Keywords:
Abstract: We consider data-driven methods for modeling discrete-valued dynamical systems evolving over networks. The spread of viruses and diseases, the propagation of ideas and misinformation, the fluctuation of stock prices, and correlations of financial risk between banking and economic institutions are all examples of such systems. In many of these systems, data may be widely available, but approaches to identify relevant mathematical models, including the underlying network topology, are not widely established or agreed upon. Classic system identification methods focus on identifying continuous-valued dynamical systems from data, where the main analysis of such approaches largely focuses on asymptotic properties, i.e., consistency. More recent identification approaches have focused on sample complexity, i.e., how much data is needed to achieve an acceptable model approximation. In this talk, we will discuss the problem of identifying a mathematical model from data for a discrete-valued, discrete-time dynamical system evolving over a network. Specifically, under maximum likelihood estimation approaches, we will demonstrate guaranteed consistency conditions and sample complexity bounds. Applications to the aforementioned examples will be further discussed as time allows.

Keywords: Adaptive and Optimal Control, Intelligent Control, Mechanical Systems Control
Abstract: This paper considers a problem of general form consensus (GFC), distributed model predictive consensus, for the orientations of mobile robots with a circular communication topology. When using the alternating direction method of multipliers (ADMM), a solution to the consensus problem is available quickly by truncating the iteration procedure. However, a smaller iteration number often results in worse control performance. This paper attempts to recover control performance by adjusting the weight of the cost function in the GFC problem. Numerical examples illustrate the effectiveness of adjusting the weight under a small number of iterations via the ADMM.

Keywords: Adaptive and Optimal Control, Modeling, System Identification and Estimation, Robust Control
Abstract: Helical motor has high thrust density and back drivability. In the previous studies, the simultaneous design of position and power-saving magnetic levitation control was extended to the reaction force control with maintaining the performance of the power-saving magnetic levitation control. This paper proposes combining a state observer to the optimal position and levitation control system. In this paper, it evaluates the complementary sensitivity function of the conventional and proposed methods. Then, it validate the performance on the numerical simulations. When the angular frequency of the observation noise due to pseudo derivative is larger than the band of the state observer, the effect of the noise can be suppressed with maintaining the performance of the position tracking characteristics.

Keywords: Adaptive and Optimal Control, Robotic and Automation Systems
Abstract: Paddle juggling is one of the simplest ball juggling, which means that a racket is hitting a ball iteratively in the vertical direction. This paper considers a hybrid approach between the feedback and feedforward ones to achieve the stability of the one-dimensional paddle juggling. We propose an adaptive rules of a sinusoidal motion of the racket, where the amplitude and phase of the racket motion are sequentially adapted at the hitting times with the gradients of the errors of the ball apex and the relative hitting time. The effectiveness of the proposed method is verified a numerical simulation.

Keywords: Adaptive and Optimal Control, Robust Control, Computer Aided Design
Abstract: In this paper, we propose model predictive control (MPC) based on a Zero-order Hold (ZOH) satisfying control input and state constraints of intersample behavior and the internal model principle (IMP). We predict the states considering model uncertainties and measurement errors, and derive a sufficient condition of constraints on sample points such that their intersample constraints are also satisfied. We clarify that the proposed MPC based on the ZOH can improve tracking performances to reference inputs while satisfying the intersample constraints, even when the state prediction errors occur.

Keywords: Adaptive and Optimal Control, Sensors and Transducers, Transportation Systems
Abstract: Among automated driving technologies, ACC (Adaptive Cruise Control), which controls the distance between vehicles and relative speed, is becoming popular. CACC (Cooperative ACC), which is an advanced ACC system, uses V2V communication and its sensors to control the distance between vehicles. Recently, cyber-attacks against automated driving systems have been studied, in which information on pedestrians or preceding vehicles obtained from LiDAR and sensors is disguised. Those cyber-attacks make it possible to obtain accurate information on preceding vehicles and pedestrians. It may lead to accident. This paper’s purpose is to develop the filtering function to reduce the impact of cyber-attacks using available information.

Keywords: Autonomous Decentralized Systems, Adaptive and Optimal Control, Computational Intelligence
Abstract: Owing to their ability to solve complex problems by breaking them down into smaller tasks, multi-agent systems (MASs) have garnered significant attention across various fields, including aero-space engineering and computer science. In MASs, the individual tasks are assigned to autonomous entities referred to as agents. To solve complex problems, each agent uses multiple inputs, such as system goals and interactions with other agents, to determine the appropriate actions. Despite their widespread applications, MASs face several challenges, including agent coordination, optimal task assignment, optimal action planning, and response to failures. This study proposes a MAS that addresses these technical issues and reports the results of applying a proposed method based on an improved objective function to the mid-air retrieval of low-speed-descent objects using an unmanned aerial vehicle system.

Keywords: Modeling, System Identification and Estimation
Abstract: This study proposed a method for dynamic graph learning using time series data obtained at nonuniform time intervals. This study formulated this problem as a convex programming problem and guaranteed that a globally optimal solution could be efficiently obtained. Additionally, the effectiveness of our method was confirmed through several numerical experiments.

Keywords: Modeling, System Identification and Estimation
Abstract: This paper proposes an identification method of network topology of consensus dynamical systems based on sparse structure learning. Assuming that the topology is binary weighted and undirected, we formulate the topology identification problem as a sparse maximum likelihood estimation problem, by employing the idea of sum-of-absolute-values optimization. For the computation, we apply a proximal gradient method and provide its closed form. The effectiveness is illustrated with a numerical example.

Keywords: Modeling, System Identification and Estimation
Abstract: In this paper, a method for identification of ARX models using block sparse estimation is proposed. While ARX models are widely used for identifying dynamic systems, determining the model order can be a challenge. In the proposed method, sparsity is simultaneously introduced to both input and output using block sparse estimation, which enables us to achieve high identification accuracy. Moreover, our method determines the model order of the ARX model simultaneously, enabling accurate and automated identification of the model structure.

Keywords: Modeling, System Identification and Estimation
Abstract: In this paper, we examine the high-probability finite-time theoretical guarantees of the least squares method for system identification of switched linear systems with process noise and without control input. We consider two scenarios: one in which the switching is i.i.d., and the other in which the switching is according to a Markov process. We provide concentration inequalities using a martingale-type argument to bound the identification error at each mode, and we use concentration lemmas for the switching signal. Our bound is in terms of state dimension, trajectory length, finite-time gramian, and properties of the switching signal distribution. We then provide simulations to demonstrate the accuracy of the identification. Additionally, we show that the empirical convergence rate is consistent with our theoretical bound.

Keywords: Modeling, System Identification and Estimation, Adaptive and Optimal Control, Mechanical Systems Control
Abstract: Although state-space representation has provided advanced and mathematical analysis in modern control theory, existence of nonconservative force in non-autonomous system prevents a simple expression of vector-matrix product in the state equation. It is because input vector cannot be expressed as a function of merely a state variable. In this study, we express a system of an 1DOF oscillator with an intermittent external nonconservative force of half-integer trigonometric functions by using a closed Hamilton system of three internal-resonance oscillators. Through the sequential unsmooth joints, each piecewise input vector is taken into a new state-space representation of a simple product of an expanded state vector with discrete-time state matrix. From this point of view, we could regard the system with nonconservative force as an intermittently closed Hamiltonian system with intermittent impulsive interactions from environment.

Keywords: Modeling, System Identification and Estimation, Identification and Estimation
Abstract: In this paper, we analyze the local identifiability of parameters in linear systems whose system matrix is given by a graph Laplacian. Graph Laplacian is a matrix given by a graph and the weights of the edges, and the weights represent the parameter in those systems. It is important to detect whether the parameter is locally unidentifiable (non-LI) a priori,since any parameter estimation methods cannot estimate non-LI parameters. To this aim, we address a problem to find the condition so that the parameter is non-LI for any initial state. Then, we obtain a sufficient condition for the parameter to be non-LI. The condition is given based on the number of vertices and edges and the number of distinct eigenvalues of the graph Laplacian. We give a system that satisfies the condition.

Keywords: Signal and/or Image Processing
Abstract: Static electricity consumption is a major cause of fatal errors in manufacturing. However, there is no established method for quantitatively evaluating invisible static electricity, which makes error detection difficult. Therefore, in this study, the luminescence of static electricity-emitting materials developed by the National Institute of Advanced Industrial Science and Technology (AIST) was imaged while varying the applied voltage, and the relationship between ``applied voltage" and ``spatial changes (primarily shape)" was investigated using HLAC and principal component analysis (PCA). It was confirmed that the extracted higher-order local autocorrelation (HLAC) can be compressed from 35 to 12 dimensions, and more than 90% of the information is included in PCA1 and PCA2. The analysis results revealed that PCA1 may extract a ``wide range of high-intensity luminescence" and PCA2 may extract ``spatial changes." Moreover, they confirmed that this information depends on the applied voltage. Therefore, a method for extracting features that can be a part of quantitative evaluation was proposed.

Keywords: Signal and/or Image Processing
Abstract: Moving object extraction is an important research area in computer vision with various applications, including gait analysis. The temporal Median filter (TMF) is a widely used technique for this purpose. The TMF can be applied to image intensities (INT) and also unit gradient vectors (UGVs). INT-based TMF and UGV-based TMF have different strengths and weaknesses. To combine these two techniques effectively, this paper proposes the automated thresholding method. The proposed method is based on Otsu’s thresholding followed by Normalized Cumulative Histogram (NCH) thresholding. We evaluate the integration framework and thresholding method on public datasets using F1-score and F2-score as evaluation metrics. Our results show that the proposed fusion method works better than the INT-based alone or the UGV-based alone approach.

Keywords: Signal and/or Image Processing
Abstract: The foreground extraction from the stationary background can be achieved by accumulating difference images (ADI) from a video sequence. We propose a novel method by applying the ADI technique to not only image intensities (INT) but also unit gradient vectors (UGV) of gray-scale images over time. We describe how these two approaches are fused. In addition, we discuss how to select the proper threshold values that are necessary for the ADI. Experimental results show the benefit of the fusion of the two approaches based on the F1 and F2 scores.

Keywords: Signal and/or Image Processing, Analytical Measurement
Abstract: In recent years, the need for maintenance of old railroad facilities has increased due to their aging. Among them are communication cables, which are difficult to locate since they are buried in the ballast. We focused on the microwave radar method, a nondestructive survey technique, in order to estimate the location of them. In this study, the effects of the ballast surface undulation and the ballast interior were analyzed by focusing on propagation time of reflected microwave, and we attempt to improvement of the SN ratio of reflected waveforms from buried objects. The surface undulation effect was restrained, but the internal effect is complex and needs to be further investigation.

Keywords: Signal and/or Image Processing, Identification and Estimation
Abstract: During times of disaster, it is important to find children who are left behind in the building. In our previous paper, a method was proposed to identify children using the features obtained from a vibration sensor installed on the floors of buildings. In this paper, a method to predict the features for the different floor materials using linear and nonlinear adaptation models is proposed. An advantage of this method is that the adaptation model can be trained using hammer-hitting data instead of actual footsteps, which are costly to collect. The experimental results show that the proposed method achieved a discrimination accuracy of 0.825.

Keywords: Signal and/or Image Processing, Identification and Estimation
Abstract: Iris recognition has long been a security verification and identification tool in the field of computer vision, frequently utilized in security and forensic science applications. However, the performance of current iris recognition systems remains unsatisfactory, particularly when capturing images under challenging conditions such as poor lighting, iris occlusion, eye misalignment, or increased distance. Despite this, recent advancements in neural network-based image recognition systems, such as convolutional neural networks (CNN), have shown the potential to tackle these problems by extracting complex features within images and delivering performance that is either comparable to or surpasses that of traditional iris recognition methods. In this paper, we proposes a novel approach that fuses iris recognition techniques with periocular information using CNN to address these challenges. Our approach was evaluated by using the CASIAIris-Thousand dataset. The evaluation results showed that the accuracy was improved from 93.64% to 99.80% compared with using the iris recognition alone. The false acceptance rate and false rejection rate were reduced noticeably from 6.30% to 0.17% and from 12.33% to 5.00%, respectively. We also discuss the potential for real-world application of such a system.

Keywords: FlowMeasurement and Control, Signal and/or Image Processing, Modeling, System Identification and Estimation
Abstract: The short paper discusses a visual nonlinear model predictive control without geometric features. First, based on a certain assumption in our previous results, a modeling method is given via the proposed basis by which the input-output linearity can be improved and thus the conventional system identification and NMPC are applicable. Second, the effectiveness of the proposed method is confirmed via the actual sloshing experiment.

Keywords: Robotic and Automation Systems, Innovative Systems Approach for Realizing Smarter World, Power Systems Control
Abstract: We have proposed and developed a mobile robot: WPT-Robot, which can move around in a living space and perform wireless power transfer to various devices. We also aim to establish an automatic power management system to operate it effectively. If the charging target was outside the manipulator's range of motion or if there was an obstacle in the trajectory, the system in the previous research could not perform charging operations. Therefore, we are improving the system to allow charging in these situations. By enabling the WPT-Robot to refer to the power transmission efficiency of the charging target, it can find the position where the power transmission efficiency is as high as possible, even in severe trajectory planning. This paper describes the specific improvements, progress, and plans for the system.

Keywords: Robotic and Automation Systems, Intelligent Control, Intelligent Systems
Abstract: This paper proposes a novel method called non-Gaussian overlapping mixtures of Gaussian processes (NGOMGP) to learn a complex policy model for real-world robotics tasks. NGOMGP models complex distribution with the multimodal regression model, sparse overlapping mixtures of Gaussian processes (SPOMGP), and distribution transformation by continuous normalizing flow (cCNF). We apply NGOMGP to learn the control policy for the robot task by imitation learning. Moreover, we investigate the influence of the hyperparameters of NGOMGP on the computation time and performance of the policy.

Keywords: Robotic and Automation Systems, Mechatronics Systems, Transportation Systems
Abstract: In this research, instead of the propeller thrust of the drone, a duct fan was applied to develop a wall inspection robot that integrates lift and pressing force. We developed a wall inspection robot using ducted fans with different thrust directions, and obtained its configuration and basic data. Improvements such as the placement of the ducted fan and the prevention of fan interference have been made, and the possibility of realizing the movement of the robot with a margin has been obtained. I checked the flow of controlling the thrust and angle of the duct fan with a block diagram by installing various sensors. In addition, we introduced a stable system that feeds back the PWM value to autonomously control the thrust of the duct fan, and confirmed that there is sufficient margin within the control range of the PWM value.

Keywords: Robotic and Automation Systems, Mechatronics Systems, Identification and Estimation
Abstract: With the rapid progress and spread of space exploration technologies, space debris has become a serious problem in recent years. The debris motion estimation technology is indispensable for the removal and recovery of space debris. This study is the basic technology to consider a small spacecraft that has ceased to function as debris and recover it. This paper reports on developing a hardware simulator for debris motion estimation, the performance of motion reproduction, and the potential of the motion estimation system using a simulated spacecraft.

Keywords: Robotic and Automation Systems, Mechatronics Systems, Simulation of Large Systems
Abstract: The proposed work on an innovative system of a delta robot combined with a spherical parallel manipulator 'SPM' has progressed through multiple stages. The conceptual design of the system was created to achieve 6-DoF motion through the hybrid parallel robot. A mechanical design was then developed using SolidWorks, which visualized the agile movement with the required angles. Furthermore, a conceptual design of the electrical layout was initiated to control the entire system in electrical and control aspects. A forward kinematic model was developed mathematically and implanted into a MATLAB script, resulting in trained data that can develop geometrical position linear and circular motion with pure and mixed multiple orientation movements. This advanced hybrid parallel robot is developed to give the ability for the delta robot to combine the position and the orientation movement. This study analyzed the kinematics of the hybrid parallel robot for precise position and orientation control, observing its movement in a square path and helix trajectory with sudden and sinusoidal wave motor angle changes. The results showed that the robot's platform moved with a pure roll angle, fixed yaw and pitch angles with repetitive roll angle changes, and a small range of roll and pitch angle with a yaw angle. These findings provide valuable insights into designing and controlling hybrid parallel robots for high-accuracy positioning, with roll and pitch angles with less than 0.2% error.

Keywords: Transportation Systems, Robotic and Automation Systems, Mechatronics Systems
Abstract: To verify the behavior of the climber with the roller arrangement, we fabricated a climber with opposed and crossed rollers and compared their operating characteristics. The roller system of the climber differs significantly between the opposed and crossed roller types, with the pushing frictional force being the main driving force in the opposed type and the transmission frictional force acting in the crossed type. From the analysis and experimental results, it was also confirmed that the crossed-type rollers raise the climber even though the pushing force is relatively small, because the frictional force that the tether snakes between the rollers and comes into contact with the rollers acts significantly. In this paper, the characteristics of each roller system based on the results from experiments and relational equations is explained

Keywords: Mechanical Systems Control, Robotic and Automation Systems, Mechatronics Systems
Abstract: This paper proposes a concept for the design and control of an energy saving manipulator utilizing passive elastic elements. Firstly, we examine the simultaneous optimization problem of storage elements and trajectories with respect to the energy consumption based on the optimal control theory. We analyze the relationship between the consumed energy and the operating time, derive a condition for the operating time to be optimal, and propose an optimal design method for elastic elements. After that, we consider the practical design problem to realize the proposed energy saving manipulator concept. A simple prototype manipulator is developed by using the linear springs and the special motor that allows the joint to rotate freely with zero torque control in order to verify the proposed method.

Keywords: Mechatronics Systems, Robotic and Automation Systems
Abstract: Manipulators are widely used in a variety of situations, due to their versatility. Direct drive motors with high backdrivability are desirable as actuators for safe use in close proximity to humans. While there is a demand for increased motor output, we review the design of integrating motors into manipulators and focus on in-link actuators, which reduce the inertia and necessary output by embedding the motor mechanism in the link itself. In this study, an in-link actuator with drive performance for use in manipulators is newly developed. The in-link actuator was compared with a motor using the same rotor and stator. The rotor and stator have sufficient power output for a robot motor, and the link has the structure of a brushless DC motor, and the inertia is significantly reduced.

Keywords: Robotic and Automation Systems, Mechatronics Systems, Mechanical Systems Control
Abstract: This paper presents a new robot design for a 6 degree of freedom (6-DOF) parallel mechanism platform that increases its workspace compared to the Stewart platform, which has a small workspace. The new design uses three fixed-length legs that connect to the platform via a revolute joint at the upper end of each leg. At the lower end of the legs, a ball joint connects to the top of three omni-directional robots, which move the lower end of the leg in a planar direction. The new motor position for the 3-wheeled omni-directional robot makes it more compact, which can further increase the platform’s workspace. Moreover, a control system is developed using inverse kinematics and encoders attached at the revolute joint for measuring leg angles. Numerical analysis shows the mechanism has a larger workspace than typical Stewart platforms, with no limitations in x and y movement and z rotation. Additionally, the paper presents the results of robot testing to follow a trajectory in x and y rotation. The testing confirms the control system’s effectiveness in controlling this type of robot mechanism.

Keywords: Mechatronics Systems, Robotic and Automation Systems, Medical and Welfare Systems
Abstract: We improved the structure of a shape-memory polymer (SMP) sheet with an embedded electrical heating wire, enhancing the manufacturing reproducibility and its durability of flexible and multi-degree-of-freedom pneumatic rubber artificial muscles. We prepared two types of SMP sheets before and after the improvement and compared the mechanical properties via bending and tensile tests. The SMP sheets were then attached to a pneumatic artificial rubber muscle, and subjected to a bending angle test and an isometric test to evaluate their bending properties.

Keywords: Mechatronics Systems, Robotic and Automation Systems, Medical and Welfare Systems
Abstract: We previously developed a variable-sensitivity force sensor that uses a cantilever made of a shape-memory polymer (SMP) sheet with an embedded electrical heating wire, the stiffness of which varies according to temperature. In this study, we improve the structure of the heating wire using computer numerical control machining. Furthermore, we fabricate an SMP force sensor with a beam fixed at both ends. Experiments using prototypes of the original and improved sensors demonstrate that the temperature distribution of the heated SMP sheet and the distance between the electrical heating wires are uniform. Moreover, we confirm that for both prototype sensors, the relationship between strain and force depends on temperature.

Keywords: Mechatronics Systems, Robotic and Automation Systems, Mechanical Systems Control
Abstract: In recent years, collaborative robots have been used to improve productivity while realizing the downsizing of factories. Many collaborative robots use a high reduction gear, which is used to achieve high torque in a small size. The back-drive performance from the load side is reduced depending on the high reduction ratio. As a result, safety in contact with the environment has become an issue. In recent years, clutch systems have attracted attention. In a clutched system, releasing the load from the geared motor reduces the load-side inertia and viscosity, which improves back-drivability. For improving the back-drivability, force control is used and a torque sensor or reaction torque observer (RTOB) is needed. In this study, we propose a RTOB for an electromagnetic friction clutch (EFC) for a series clutch actuator (SCA), which is a clutch at the end of the geared motor. This paper shows that the RTOB of EFC is more sensitive than that geared motor. The high sensitivity of the reaction torque performance is expected to enable higher back-drivable torque motion.

Keywords: Human-Machine Systems, Human Interfaces
Abstract: Recently,research has been conducted on mixed reality (MR),which provides immersive visual- ization and interaction experiences,and on mapping human motions directly onto a robot in a mixed reality (MR) space to achieve a high level of immersion However,although the robot itself is mapped onto the MR space,the robot’s environment itself is not mapped, making it difficult to comfortably perform tasks that require detailed manipulation or manipulate objects that are difficult to see from the human perspective. Therefore,we propose a system in which the environment around the robot itself is also mapped on the MR space, and operations can be performed on the MR space, enabling immersive real-space operations.

Keywords: Human-Machine Systems, Human Interfaces
Abstract: The smart suit is a device that passively assists human movement and relieves the burden on the waist through elastic elements. It is possible that it has an improvement effect on keeping body balance through sensory feedback system. In previous study, the analysis of center of pressure (COP) in static upright posture confirmed the positive impact of the smart suit on the sensory feedback system. However, this method cannot evaluate the assisting effect of the smart suit on keeping balance during movement. This paper proposes a sensory feedback control model based on zero moment point (ZMP) and evaluates the impact of the smart suit on the sensory feedback system during squat. We also discussed the effectiveness of the proposed method by comparing the analysis results of squatting exercise between previous methods and the proposed method.

Keywords: Human-Machine Systems, Human Interfaces, Entertainment Systems
Abstract: Most Question-answering (QA) systems rely on training data to reach their optimal performance. However, acquiring training data for supervised systems is both time-consuming and resource-intensive. To address this, in this paper, we propose TFCSG, an unsupervised similar question retrieval approach that leverages pre-trained language models and multi-task learning. Firstly, topic keywords in question sentences are extracted sequentially based on a latent topic-filtering algorithm to construct unsupervised training corpus data. Then, the multi-task learning method is used to build the question retrieval model. There are three tasks designed. The first is a short sentence contrastive learning task. The second is the question sentence and its corresponding topic sequence similarity judgment task. The third is using question sentences to generate their corresponding topic sequence task. The three tasks are used to train the language model in parallel. Finally, similar questions are obtained by calculating the cosine similarity between sentence vectors. The comparison experiment and ablation experiment on public question datasets that TFCSG outperforms the comparative unsupervised baseline method. And there is no need for manual marking, which greatly saves human resources.

Keywords: Human-Machine Systems, Human Interfaces, Social Systems
Abstract: In recent years, robotics technology has advanced and humanoid robots have been developed. However, when it comes to the motion of the arms that work directly, it is necessary to create human-like motion in order to avoid causing fear or discomfort to observers. To solve this problem, research has been conducted on generating human-like motion by using machine learning based on human motion. However, this method lacks data for postures that are impossible for humans to take, and the human-likeness of reproduced postures in that area is compromised. Therefore, this paper describes a method for generating movements that ensure human-likeness even in areas where humans cannot take postures by using questionnaire answers.

Keywords: Human-Machine Systems, Intelligent Systems
Abstract: When developing devices or systems to assist with a task, often the physical and cognitive aspects are considered separately. However, previous studies have shown that the cognitive load of a task interacts with the physical load experienced by the user and vice versa. Therefore, there may be benefits to considering both aspects at the same time. In this study, we explore an in-series human-robot cooperation arrangement to provide simultaneous cognitive and physical assistance, where the user is upstream from a downstream smart assistive robot. In this arrangement, the human user can focus on the high-level aspects of a task while delegating both the physical and cognitive components of the lower-level aspects to a downstream smart robot. A prototype was developed, and an experiment was conducted to explore this human-robot cooperation concept.

Keywords: Human-Machine Systems, Intelligent Systems
Abstract: Cooperation between humans and robots is essential to improve work accuracy and efficiency and save labor. Artificial Intelligence robots are superior to humans in terms of high-speed decision-making and smooth movements. By contrast, humans are superior to robots in their ability to respond flexibly to changing circumstances. In this study, we developed a wearable robotic manipulator with a co-thinking manipulation system to support human-robot collaboration in intelligent tasks toward a single goal. In the proposed system, the human user and the robot are involved in the same packaging problem. The robot can assist the human user in the packaging task, while the human user can operate the robot or stop the task at any time. Finally, this study explores a mechanism for maximizing collaborative performance in a human-robot control system.

Keywords: Guidance and Flight Control
Abstract: This paper explores a novel approach for deriving target angle correction commands in rhumb line control, a widely-used attitude control method, in JAXA’s sounding rocket S-520-RD1. To fulfill strict attitude requirements during the flight of S-520-RD1, radio guidance is implemented to rectify the target angle of the rhumb line control. We introduce a sensitivity matrix that can compute the correction command using radar tracking data, and propose a way to derive the matrix from a pre-determined nominal orbit. To account for command resolution limitations and wind-related effects, we verify the effectiveness of our proposed method through the Monte-Carlo simulations. Furthermore, we present the flight result of the S-520-RD1 using our method, which demonstrates precise attitude control.

Keywords: Guidance and Flight Control, Identification and Estimation, Mechanical Systems Control
Abstract: In this report, an attitude control system with magnetic torquer for ultra-small satellite called as “cubesat” on polar orbit is described. The authors conduct a passive attitude control system by using magnetorquer consisted of permanent magnet arranged in a circle for geomagnetic field on polar orbit. Then the proposing passive attitude control system for the small satellite is brought as COTS to adapt such strict conditions for equipment space and electric power supply. To confirm the constructing passive attitude control system for the small satellite, some preliminary experiments to obtain the characteristics of constructing magnetic torquer are executed on ground. Moreover, experiment of attitude control on polar orbit as Inovative-2 project are executed. As a result, it is considered that the proposing passive attitude control system with magnetic torquer is effectiveness for the small satellite.

Keywords: Guidance and Flight Control, Intelligent Control, Transportation Systems
Abstract: This work considers the consensus problem of multi-agent systems with high-order dynamics. When the dynamics of each agent are expressed by multiple integrators, the behavior after achieving consensus is denoted by high-order differential equations, which means that we can design consensus dynamics by selecting the coefficients of the differential equations which indicate the behavior after achieving consensus. This work considers the sparse controller of multi-agent systems with second-order dynamics to realize the desired consensus dynamics. The consensus condition for the second-order multi-agent system with a feedback controller is denoted by a linear matrix inequality (LMI). Thus, the sparse controller design problem for the consensus is approximately formulated as the semidefinite programming problem.

Keywords: Guidance and Flight Control, Transportation Systems, Intelligent Systems
Abstract: Automated parking technology is becoming increasingly popular to assist non-skilled drivers with park- ing. However, these systems face challenges when utilized in narrow spaces where precise collision avoidance is re- quired. Most conventional studies approximate the controlled vehicles as circles, ellipsoids, or other shapes, which makes generating paths difficult in narrow spaces due to excess margin. To solve this problem, a new approach is proposed that uses non-linear transformations to describe collision avoidance constraints among rectangles on a manifold within the model predictive control (MPC) framework. This approach reduces the computational cost of optimization calculations compared to some conventional shape-aware collision avoidance methods. This study validated the usefulness of the proposed method by conducting tests on an actual vehicle. The results confirmed that our method enables automated parking in very narrow spaces in real-world applications.

Keywords: Nonlinear Control, Mechanical Systems Control, Guidance and Flight Control
Abstract: This paper considers a global feedback design for the avoidance of dynamic obstacle avoidances for a holonomic mobile robot as an application of nonlinear systems defined on time-varying manifolds. The proposed global feedback control consists of two parts: a coordinate transformation and a conventional global controller for nonlinear systems defined on time-invariant manifolds. The transformation enables the mapping of the dynamic obstacle avoidance problem to a static obstacle avoidance problem for controlling the relative position; the conventional controller can stabilize the origin of the systems defined on the time-invariant manifolds. Using an example, we demonstrate that the control of the static obstacle avoidance problem may not imply the control of the dynamic obstacle avoidance problem. The proposed method considers the effect of the coordinate transformation and asymptotically stabilizes the desired equilibrium of the closed-loop system of the obstacle avoidance problem.

Keywords: Robust Control, Multivariable Control, Guidance and Flight Control
Abstract: In this paper, a second-order multi-agent consensus via relative displacement feedback is studied. It is assumed that the velocity measurements of the agents are not available and that the position information processing is affected by a uniform bounded delay. A sufficient condition for consensus in undirected and connected topologies is provided in terms of a complex stability region for the eigenvalues of the Laplacian matrix. Moreover, a method for the evaluation of the critical delay is presented. Numerical examples illustrate the effect of the delay in different topologies.

Keywords: Robotic and Automation Systems, Innovative Systems Approach for Realizing Smarter World, Transportation Systems
Abstract: This paper proposes a Micro-Logistics Platform to automate shelf management in retail stores and optimize product placement for all customers. The proposed system includes a Micro-Logistics Node (MLN), delivery robots, flapping drones, ports, and edge servers, all connected through 5G networks. Products are packed in small trays at a suburban distribution center, transported to the port, loaded onto delivery robots, and moved to the MLN for display. Customers can order products via smartphone, which are then loaded onto delivery robots or flapping drones for delivery. Multiple MLNs can function as automated display shelves in stores or small unmanned stores in buildings. The proposed system has the potential to reduce the workload of store clerks, and improve the shopping experience for all people.

Keywords: Robotic and Automation Systems, Computational Intelligence, Intelligent Systems
Abstract: This paper proposes a 3D space sensing system and path planning method for autonomous robots in unknown environments. Using Growing Neural Gas with Different Topologies (GNG-DT), the system learns the topological structure of feature attributes for environmental perception. It is utilized in various robot applications such as object clustering and path planning. The study introduces a spatial perception system that is integrated with internal sensors. The use of adaptive 3D space sensing is increasingly important for autonomous robots in various fields.

Keywords: Intelligent Systems
Abstract: We present here two examples of simple mathematical models of self-driven agents. The first example is a simple model of an on-demand transporter, while the second example explores the collective behavior of a group of agents in the context of pursuit and evasion, which we refer to as ”Group Chase and Escape.” Both models exhibit unexpected emergent behaviors that may have relevance to real systems. The insights gained through theoretical models can aid in predicting and controlling these systems with emergent behaviors.

Keywords: Intelligent Systems, Nonlinear Control, Intelligent Control
Abstract: In this paper, we propose a stabiling controller design based on Takagi-Sugeno fuzzy model for four-wheeled vehicle. Four-wheeled vehicle is modeled as a non holonomic system, and is known to be difficult to stabilize by continuous-time state feedback controller. To design controller by state feedback control, the vehicle model is converted into a chained form, which is one of bilinear systems. Then it can be written as a Takagi-Sugeno fuzzy system which can generally represent nonlinear systems. The converted dynamical fuzzy system makes it possible to handle nonlinearity of the four-wheeled vehicle directly, and then the asymptotic stability is guaranteed by Lyapunov stability theorem. Finally, simulation examples show the effectiveness of our proposed controller design method.

Keywords: Robotic and Automation Systems
Abstract: Recently, robotics middleware has been widely used. However, a software module that runs on one middleware does not run on another middleware. To solve this problem, the interoperability of software module is important. However, if the middleware has the function for interoperability, how to apply the function for different middlewares are also important. Thus, we propose a system design for interoperating diffrent middlewares based on OpenRTM-aist. In this paper, the manipulation tasks is focused as target task. We evaluated proposed system design on different middlewares and also different robot to show the flexibility of proposed system design.

Keywords: Intelligent Systems, Innovative Systems Approach for Realizing Smarter World, Human-Machine Systems
Abstract: The recent successes of deep learning in Natural Language and Computer Vision tasks have led to an increasing interest in tasks involving Multi-Modal learning. One such task is Outdoor Visual Linguistic Navigation, where a combination of language and vision input is given to express a navigation instruction in outdoor scenes. Presently the end-to-end deep learning models proposed for such tasks lack in the ability to perform Commonsense Knowledge-based reasoning. In this work, we propose a method to use Knowledge Insertion as a strategy to mitigate the lack of Commonsense Knowledge. Our experiments show that this strategy leads to increase performance in the task of Commonsense Knowledge-based reasoning for Outdoor Visual Linguistic Navigation.

Keywords: Multivariable Control, Adaptive and Optimal Control
Abstract: In this paper, we report an improved method for a distributed implementation of model predictive control (MPC) on multiple low-resource IoT devices. The use of non-uniform splitting of the prediction horizon in the parallel MPC method allows each IoT device to have a subproblem with a different length of shotened prediction horizon. This feature gives flexibility in the size of the subproblem, which leads to overall perfomance improvement of the proposed parallel MPC method. The effectiveness of the proposed method is verified on a popular microcontroller board, micro:bit.

Keywords: Adaptive and Optimal Control, Robotic and Automation Systems, Nonlinear Control
Abstract: This paper studies a sample-based model predictive control using the Monte Carlo sampling method. Different from gradient-based Model Predictive Control (MPC), Monte Carlo Model Predictive Control (MCMPC) is able to introduce discontinuous phenomena such as collisions into the system. This feature makes it suitable for the control of underwater snake robots to explore complex and narrow spaces and interact with the environment when operating rescue missions. Curvature Derivative Control (CDC) is utilized to reduce the control inputs from each joint to only the head joint which optimizes the lateral undulatory locomotion of the snake robot and mitigates the complexity of MCMPC calculation. Collision is introduced into the system as a Linear Complementarity Problem (LCP), which allows MCMPC to respond to collisions in the prediction stage. Simulation results showed that the snake robot can generate various gait patterns and accomplish obstacle-aided locomotion by taking obstacles into account. The robot can reach the target area by adding positional error between the center of mass of the snake robot and the destination into the cost function.

Keywords: Mechatronics Systems, Adaptive and Optimal Control, Transportation Systems
Abstract: The drive systems of Hybrid Electric Vehicles have been studied to design a control that can optimize fuel consumption. This study addresses controller design for Model Predictive Control using novel weighting coefficients. The proposed method makes the coefficients variable according to driving conditions, i.e., varying the weighting effects at the stage of decreased speed. In this paper, the validity is compared for fuel consumption using 3 driving cycles then the proposed method is a higher value than the conventional MPC in all cycles.

Keywords: Adaptive and Optimal Control
Abstract: In this paper, we propose a control system for wheelchairs to enable automatic trajectory generation. The whole system not only allows the wheelchair to complete the trajectory generation while avoiding pedestrians, but also allows pedestrian to avoid the wheelchair when they see it.

Keywords: Mechanical Systems Control, Adaptive and Optimal Control, Mechatronics Systems
Abstract: Leg/wheel mobile robots can achieve proper load distribution of wheels equipped at the tip of articulated legs. This enables autonomous tracking on rough terrain without getting stuck or tipping over. To reduce the computational cost due to high joint degrees of freedom, we propose a distributed model predictive control (DMPC) that takes into account the wheel load ratio. Cooperative behavior among the partitioned models is considered by constraint conditions. The load distribution control also uses variables of other partitioned parts. In the proposed method, sequential optimization tracks the solution. In this research, the performance of the controller was evaluated by physical simulation using multi-body dynamics. The results indicate that proper load distribution can be achieved through distributed model predictive control.

Keywords: Signal and/or Image Processing, Identification and Estimation, Guidance and Flight Control
Abstract: This paper presents a tracking algorithm for an unknown and variable number of pedestrians observed by LiDAR based on k-means clustering enhanced by joint probabilistic data association filter (JPDAF). k-means clustering partitions the point cloud data into a specified number of clusters with a minimum variance on each cluster. It is specifically powerful to separate multiple clusters nearby, provided the number of clusters is known. It is difficult, however, to know the number of clusters in advance in open areas. In this study, we combined JPDAF, which tracks multiple target detections, and k-means clustering to deal with changes in the number of pedestrians. Finally, the verification results using data acquired in a real congested environment showed that the system could detect and track multiple nearby pedestrians.

Keywords: Advanced Computics, Modeling, System Identification and Estimation, Process Control
Abstract: A Digital Twin is a simulation model that accurately imitates the behavior of a physical system in real time. A Process Digital Twin can facilitate intelligent decision-making at the plant operation level, enabling operators to increase plant productivity. It automatically monitors plant performance by reviewing data from across the plant, providing guidance to operators to improve performance and productivity without the need for engineering staff. To address problems that arise from process simulation-based Digital Twins, this work employs surrogate models for the development of Process Digital Twins that are used for plant operations decision-making and optimization. Surrogate models are simple statistical models that mimic the input/output behavior of complex systems. In this study, a surrogate model is formulated to estimate the performance of a heat exchanger in terms of heat duty, heat transfer coefficient, etc. A training data set containing over 9,000 points is used to build the surrogates, while a testing data set of 1,000 points verifies their accuracy. The surrogate model is shown to be sufficiently accurate to be employed in operators' decision-making applications, such as optimization and control.

Keywords: Modeling, System Identification and Estimation, Identification and Estimation, Multivariable Control
Abstract: This paper proposes a method for estimating the uncertainty in the frequency domain of the estimate obtained by the authors' previously proposed identification method. The estimation of the pseudo-covariance matrix as well as the covariance matrix of the transfer function matrix can reduce the conservatism of the estimated uncertainty in the frequency domain. In the numerical example, the estimated standard deviations of gain and phase plots in the proposed method are compared with the standard deviations obtained from the covariance alone and the sample standard deviations of gain and phase plots and the usefulness of the proposed method is demonstrated.

Keywords: Modeling, System Identification and Estimation, Identification and Estimation, Signal and/or Image Processing
Abstract: We derive the computational complexities of our recursive subspace state-space system identification algorithm (R4SID) and the existing R4SIDs. Furthermore, we clarify that the computational complexity of our R4SID is less than that of the existing R4SIDs based on the LQ-factorization. Finally, effectiveness of computation time and accuracy of our R4SID is statistically examined through numerical experiments.

Keywords: Modeling, System Identification and Estimation, Mechanical Systems Control, Nonlinear Control
Abstract: In this study, we consider a modeling problem associated with belt-driven robots that transfer silicon wafers in the automated manufacturing of semiconductors to achieve high-speed and high-precision transfer control. We propose 1) a modeling method for the belt-driven robot that takes into account the dynamics of the belt and the static friction force, and 2) a calculation method for the static friction force. Using simulation experiments we confirmed that the proposed model can reproduce the actual trajectory deviation phenomenon that is observed in actual robots.

Keywords: Modeling, System Identification and Estimation, Power Systems Control, Simulation of Large Systems
Abstract: When using digital twins to create a simulation in the cyber space, their plant models must sequentially predict physical phenomena such as energy and water. However, increase in calculation costs renders their execution in real time challenging in case of a large scale, and they must be executed with high accuracy. Employing the mainstream technique of reducing the computational cost involves data-driven modeling, which suffers limited extrapolation accuracy as it does not have a physical structure. This study derived the simultaneous physical equations of the microgrid electric power network for three-phase voltage imbalance of AC electric power. Further, simulations were performed based on the equations. Using this power network model, we demonstrated that reduced-order modeling techniques with physical structure can offer better accuracy than models without a physical structure.

Keywords: Modeling, System Identification and Estimation, Robust Control
Abstract: We have proposed a vehicle driving model that is robust against road geometry and environmental disturbances. Our proposal model is based on a two-wheeled model, the error in the position and azimuth angle of the center of gravity point that occurs in two-wheeled model is expressed by the deviation between the front wheel steering angle (lateral direction) and the velocity (longitudinal direction), and this deviation is estimated adaptively using a three-layer Neural Network. We are considering applying this proposed method to a real system (Electric senior cart). In order to design a control system using this vehicle driving model in an actual system, it is necessary to have a specification that shows the relationship between the correction parameters in the longitudinal direction and the lateral direction. Therefore, in this study, in order to clarify the relationship between these correction parameters and speed/wheel steering angle, we drive a vehicle in a steady circular turn on vehicle motion analysis software CarSim.

Keywords: Signal and/or Image Processing, Identification and Estimation, Human Interfaces
Abstract: Motor imagery is one of the paradigms of Electroencephalography(EEG)-based Brain-computer interface to input of operation intention. There is theoretically difficult to decrease the processing time while maintaining sufficient accuracy in the Conventional method. In this paper, we focused on the high-speed response of the observer and attempted to the fast detection of the alpha and beta band amplitude using a periodic disturbance observer. We implemented the Observer and input virtual signals that mimic brain waves, and a raw EEG signal. The responses show that the periodic disturbance observer can estimate the steady state within a sufficient short speed.

Keywords: Signal and/or Image Processing, Biological and Physiological Engineering, Sensors and Transducers
Abstract: Holter electrocardiographs, which are generally used for long-term ECG(electrocardiogram) measurement, are not necessarily suitable for long-term measurement during sleep because of discomfort and restraint due to the direct attachment of electrodes to the skin. An alternative to address this problem is non-contact ECG measurement using capacitively coupled electrodes on the skin. Then, Nakamura et al. designed and implemented a new sensor that can measure both body position and ECG with a common array electrodecite{nakamura}. In ECG measurement using the sensor, it is easily affected by body motion and contact conditions due to postural and positional changes. So, it is necessary to select the appropriate approach for ECG measurement again when affected by these changes. To solve this problem, we attempted to develop a method to automatically select electrode positions suitable for ECG measurements from the silhouette.This paper presents an example of effective electrode selection in the supine position.

Keywords: Signal and/or Image Processing, Identification and Estimation, Analytical Measurement
Abstract: The purpose of this study is to develop a pose estimation method using a single general camera for the measurement and analysis of sprint form data in athletics, making it easier to perform. Previous sprint form analyses required the use of measuring instruments attached to the body or special equipment and facilities, but analysis using pose estimation from camera images that do not require measuring instruments attached to the body has made it possible to measure more easily. In this study, we aim to enable analysis of the 100m sprint, which is general short-distance race with a single camera, which was difficult with conventional methods, by using super-resolution technology to make pose estimation possible even at a distance. This paper describes the pose estimation method, outlines the developed method, presents the results of the effectiveness verification experiment of the proposed method, and concludes with a summary and future prospects.

Keywords: Signal and/or Image Processing, Ubiquitous Healthcare, Medical and Welfare Systems
Abstract: The number of people with physical disabilities in Japan is increasing, and wheelchairs are among their main support tools. Since wheelchair users are at risk of serious injury depending on their physical function, researchers are investigating ways to prevent people from falling out of them. Most fall prevention research has focused on electric wheelchairs, but manual wheelchairs are also widely used because they prevent disuse muscle atrophy of users. Therefore, a fall prevention system that allows users to remain physically active is necessary. Conventional obstacle detection systems have difficulty detecting small obstacles that are dangerous for wheelchair users, and in some cases detection is impossible depending on the distance. Therefore, in this research we propose an algorithm that can measure distance and height regardless of the actual distance to, and size of, the obstacle. This algorithm identifies distance and height by specifying the range irradiated to the obstacle based on the light intensity information of the irradiated line laser. To verify the algorithm ’s effectiveness, we measured the distance to an actual obstacle that was 20 mm high, which is the standard for the height that a wheelchair can climb over.

Keywords: Signal and/or Image Processing, Intelligent Systems
Abstract: The particle filter is a highly robust object tracking method because it predicts the motion of the tracked object using a state transition model. However, it is difficult to continue the tracking when the object moves differently from the transition model. Therefore, we propose a particle filter with a convolutional neural network (CNN) for person tracking. CNN estimates the displacement of the target from the rectangle region of a person to be tracked. The estimated displacement is incorporated to the transiton model. Hence, we can track the targets even if it chenges the motion phase. Experimental results demonstrate the effectiveness of the proposed method for a person tracking.

Keywords: Signal and/or Image Processing, Intelligent Systems, Robotic and Automation Systems
Abstract: This paper proposes a method that can improve the performance of multi-object tracking by modifying the Kalman filter which is used to estimate the state of the objects in the video sequence and matching strategy to prevent objects obtained at the current frame in the video sequence from being associated with the wrong trajectory. The Kalman filter used in multi-object tracking is conventionally structured to use only bounding box location information as an observation system. To improve the accuracy of the filter estimation, we added velocity information derived from the difference of positional measurements to the observed data and introduced a process in which the observation noise covariance varies with the confidence score of the object detection. This enables tracking that is more nearly ground-truth. We also introduced gating as an improvement of the matching strategy. Gating is configured to compare the speeds that each track of the object and the matching candidate of the results of object detection with the Euclidean distance, and if this distance exceeds a threshold, the matching is canceled. The proposed method is introduced ByteTrack, which is the base of several object tracking methods reported in recent years. As a result, we achieved 90.1 MOTA, 83.7 IDF1, and 0.117 MOTP on the training set of MOT17.

Keywords: Intelligent Systems, Signal and/or Image Processing
Abstract: In this study, we propose a vehicle tracking system targeting drone footage. The proposed system utilizes the real-time object detection network, YOLOv5, to acquire vehicle location information and segment the vehicle regions based on it. The system analyzes the histogram of the segmented regions, compares them with past frames, and determines whether the objects are identical to perform tracking. To enhance the efficiency of histogram comparison, the algorithm is designed to compare objects only within a certain radius using coordinate information and past frame object data. The MOTA (Multi Object Tracking Accuracy), a representative tracking evaluation metric, showed 90%. However, it is important to consider the limited environment of data usage and experiments. The results of this study suggest that the real-time performance of the vehicle tracking system can be utilized in various fields such as traffic control, vehicle management, and accident response.

Keywords: Robotic and Automation Systems, Signal and/or Image Processing, Entertainment Systems
Abstract: Automation of line judgment in tennis enhances the fairness of the game. However, conventional judgment assistance system based on three-dimensional trajectories can cause discrepancies with the actual bounce mark of the ball. Therefore, we propose a ball mark visualization system using high-speed drop location prediction and preceding mirror control. High-resolution imaging toward the predicted drop location using rotational mirrors facilitates visualization of the ball mark simply by comparison with the image after bouncing. We have experimentally evaluated an accuracy of the drop location prediction and response performance of the rotational mirrors. We also demonstrated the validity of the ball mark visualization on artificial turf.

Keywords: Intelligent Control, Robotic and Automation Systems, Intelligent Systems
Abstract: The article introduces a potential field method called Improved Interfered Fluid Dynamical System (IIFDS) for path planning in dynamic environments. The goal of this approach is to enhance generalization in dynamic environments.To address the challenges posed by changes in the environment, the article proposes a Self-adaptive Deep Reinforcement Learning (SA-DRL) method. The SA-DRL method employs an actor-critic structure to train the actions for the IIFDS controller. The proposed method is tested in dynamic environments, and the results indicate that it is capable of adapting to such environments

Keywords: Mechanical Systems Control, Robotic and Automation Systems
Abstract: This study develops a method to calculate the motion of a given plant model along a specific path which is achieved by an integral form in a single run without iterations. Simple algorithms and methods are implemented to show the capabilities and extension possibilities of this approach. By using an example path and plant model, simulation results show the effectiveness of this approach.

Keywords: Robotic and Automation Systems, Sensors and Transducers
Abstract: Robotic odor source localization is difficult, particularly in obstacle regions, owing to the challenge of constructing a plume model. Without the model, robust search algorithms such as Infotaxis can not be fully utilized. Therefore, we propose a novel approach that involves dividing the environment into sub-areas and utilizing a coarser map resolution in addition to the resolution of the Infotaxis algorithm. This approach seamlessly switches between the Infotaxis and Dijkstra algorithms, resulting in a higher success rate and reduced search time for odor source localization in obstacle regions, as demonstrated by our mobile robot experiments.

Keywords: Robotic and Automation Systems, System Engineering, Signal and/or Image Processing
Abstract: For high-value precision agriculture, monitoring plant growth trends, pest and disease control, and automation processes will standardize operations and increase yield while reducing losses as much as possible. In greenhouse scenar- ios, one method for monitoring plant growth requires localization, modeling, and post-processing of the plants. However, recognizing and extracting the root position of the plant is difficult for a robotic arm. To overcome this challenge, this paper uses a marker-based localization method to provide the root position directly. After acquiring and iteratively registering the point cloud, the main stem of the plant is extracted for future plant organ segmentation and clustering. Nevertheless, extracting the main stem is a complex task, and although there are studies on skeleton extraction for ordinary trees or wheat, there are few solutions for high-wire plant stem extraction. Therefore, an optimized geometric-based stem extrac- tion algorithm (SEA) can extract the stem point cloud with a high success rate under conditions no matter whether the cloud is intact or the main stem region is occluded.

Keywords: Robotic and Automation Systems, Nonlinear Control
Abstract: This paper proposes a control method for bipedal walking using a compass-type telescopic-leg model. The main idea is to achieve energy control for locomotion through the kick motion of the rear support leg at the end of the double support phase. Computer simulations confirm that the compass-type walk can be achieved by controlling the energy to the desired value at the beginning of the double support phase.

Keywords: System Engineering, Autonomous Decentralized Systems, Intelligent Systems
Abstract: In this paper, a fall determination and prediction system is developed to avoid falls of multi-legged robots. The system consists of two algorithms. One is a fall determination algorithm that uses support polygonal pillars to determine the situation in which the robot will fall over. The other is a fall prediction algorithm, which can predict falls in advance by using mechanical energy conditions. The effectiveness of the proposed system was evaluated through experiments in which an external force was applied to a stationary robot to make it fall over.

Keywords: Components and Devices, Mechatronics Systems, Mechanical Systems Control
Abstract: In this report, an antenna deployment system by using convex tape for ultra-small satellite is conducted. The antenna deployment system as passive control system without electric actuator is proposed with adapting the strict small satellite condition constrained as electric power being so low and equipment space being so narrow. Then the extension behavior of the antenna deployment system is executed by restoring force of convex tape. In this report, two type antenna systems as dipole antenna and Yagi antenna are conducted, furthermore the two antenna deployment systems are equipped to two cubesats as Innovative satellite technology demonstration program. To confirm the effectiveness for the constructing antenna deployment system, some experiments such as aquation of characteristics of radio waves receiving and deployment function are executed, the obtained results are evaluated.

Keywords: Intelligent Control, Mechanical Systems Control, Autonomous Decentralized Systems
Abstract: This paper applies a method of resilient consensus to the orientations of mobile robot agents by using the Weighted-Mean-Subsequence-Reduced (W-MSR) algorithm. The orientations can reach a consensus under a communication structure despite non-cooperative agents. Finally, experiments demonstrate that the orientations of the mobile robot agents can reach a consensus.

Keywords: Mechanical Systems Control, Mechatronics Systems, Robust Control
Abstract: Vibration suppression has attracted interest in achieving fast, stable motion control in industrial fields. This study focuses on the wave partial differential equation (PDE) for modeling mechanical resonant systems. The wave PDE is obtained by assuming the spring-mass elements are distributed in one-dimensional space. Its solution provides two kinds of matrix representation. One is effective for descriptions of cascade coupling, and the other is a causal representation consisting of transfer function elements. This study proposes a vibration suppression method using the PDE model connected to a tip load. Moreover, the matrix representation derives a basis transformation of physical quantities. The PDE model allows us to consider the vibration factor as wave reflection. The controller cancels the amount on a reflected wave basis and regulates that on a traveling wave basis. The suppression method requires only the PDE part's distributed parameter, making the control system resistant to inertial variations.

Keywords: Mechanical Systems Control, Micro and Nano Devices, Opto-Electronic Measurement
Abstract: The scoring competition represented by gymnastics has a particularly high demand for accuracy and fairness of judgment. Fujitsu Limited has been developing Gymnastics Judging Support System using MEMS mirror type 3D laser sensor in collaboration with the International Gymnastics Federation and the Japan Gymnastics Association, and officially started operation in some events from the 2019 World Championships. MEMS mirrors are typically driven at the same frequency as their mechanical resonance frequency. Since the amplitude and phase fluctuate greatly with changes in resonance frequency, it is important to control the rotation angle to keep the amplitude and phase accurate. This paper describes the modeling, controller design and simulation results of the MEMS mirror.

Keywords: Mechanical Systems Control, Modeling, System Identification and Estimation
Abstract: Compass-like biped robots are biped robots with no knees. They are useful for investigating walking dynamics, since they are simple and capture the essence of walking, especially passive dynamic walking. Passive compass-like biped robots have angle limiters in some experimental arrangements, and the relative angle between the two legs is limited. For a compass-like biped robot with an angle limiter, an impact occurs at the time of collision between the limiter and a leg, but its dynamics have not been modeled yet. Therefore, the effect of the angle limiter is unclear, while it is experimentally known that the angle limiter improves walking robustness for passive dynamic walkers. This paper provides a mathematical model of dynamics at the impact time of collision between the limiter and a leg of a compass-like biped robot. The obtained model helps to analyze the limiter effect of compass-like biped robots computationally and/or theoretically. It may be useful for understanding the dynamics of bipedal walking and for generating human-like biped locomotion.

Keywords: Mechanical Systems Control, Multivariable Control, Robust Control
Abstract: This paper denotes the adjustment policy of the LADRC parameters that theoretically guarantee the stability of the continuous-time cascaded LADRC for the inverted pendulum on a cart. The system stability is guaranteed by the Routh–Hurwitz stability criterion, and the motor voltage constraint is considered by the objective evaluation index with respect to an integral of time absolute angle. The effectiveness of this method can be confirmed by performing numerical simulations, which is set optimal cascaded LADRC parameters. That is, the cart displacement and the pendulum angle can be obtained faster response within rated voltage.

Keywords: Human-Machine Systems, Modeling, System Identification and Estimation, Electrophysiology and Kinesiology
Abstract: Forward dynamics simulations have the advantage of assessing performance of novel exoskeleton designs at a low cost. For developing a new passive lower-limb exoskeleton, the simulation needs to represent the sitting posture in which the wearer performs working tasks while maintaining balance with the whole body. The present study constructed a forward dynamics simulation for analyzing and developing a new passive lower-limb exoskeleton; the validity of the simulation was investigated using experimental data. The present method computes the interactions between the exoskeleton and wearer, such as reaction forces, physical posture, and physical load, based on the forward dynamics simulation driven by nonlinear model predictive control (NMPC). The NMPC cost function consisted of the physical load and the fitness of working task with constraints to evaluate balance. As a result, the present simulation represented the characteristic posture when sitting on the exoskeleton in which the wearer performs the working task while maintaining balance with the whole body. However, the simulation computed an upright posture of the lumbar joint that differed from the experimental results and needs to be improved. In future work, the simulation will be modified for representing the valid physical posture when wearing the exoskeleton, such as simulating the physical motion of the same working task as in the experiment, and modeling the interaction between the human, exoskeleton, and ground.

Keywords: Human-Machine Systems, Robotic and Automation Systems
Abstract: The demand for automated Personal Mobility (PM) and its applications called Mobility as a Service (MaaS) are growing. Because the PMs sometimes share their mobile space with the surrounding pedestrian, PMs have to take the surrounding pedestrian’s behavior into account to ensure safety and social acceptance. To achieve this, PMs require the prediction model of the pedestrian. This paper presents the construction of the prediction model of the surrounding pedestrian’s intention, specifically the choice of whether to give way or not. At first, the amount of walking behavior with the interaction among the pedestrians are measured in the experiment. In the experiment, the intention of the pedestrian is measured directly with the switch device in real time. This intention can not be measured in the observation camera nor big data in a real environment while the information is essential to build the decision-making model because the decision timing is not always the same as the motion changes. The explanatory variable for the model is discussed based on the analysis of the measured data, and the decision-making process is modeled by the logistic regression model. Finally, the prediction performance is tested with cross-validation.

Keywords: Mechatronics Systems, Human Interfaces, Human-Machine Systems
Abstract: The purpose of this research is to develop a control system for a social robot with a soft exterior that interacts with the human by taking advantage of the characteristics of its exterior. The social robot is expected to be used for presentations, as it is expected to change inorganic robot communication into something more appealing to people. We developed a system that guides a subject to an object or a place based on the characteristics of the robot, such as having a real body, a robot arm, and the ability to communicate with people and conducted a preliminary experiment.

Keywords: Mechatronics Systems, Human-Machine Systems, Modeling, System Identification and Estimation
Abstract: Intuitive haptic feedback is a major hurdle that needs to be overcome to deliver prosthetic devices fit for daily use. Current preferred non-invasive feedback methods lack the natural feeling that can be provided by mechanotactile feedback systems. However, these systems are often bulky and cannot serve as a daily life accessory to a prosthetic hand. In this research, we present a wearable non-invasive haptic feedback device designed around the concept of an easy-to-visualize and interpret mapping between the sensation in the prosthetic hand and stimulation provided by the device. The proposed system maps sensation from five fingers in the prosthetic hand to five fingers in the feedback device and is designed to provide the feel of a hand touching the user's upper arm. The stimulation is cutaneous, targeted at the skin on the upper arm, and, felt as pressure with additional stretching and squeezing cues at high outputs. A model of the device is developed from the kinematic relations and is used to investigate the dependencies and optimize the design parameters in the context of delivering haptic force feedback with desired motion profiles. Our results indicate that the haptic armband is capable of providing feedback that can be customized to meet different user preferences. We expect this device to be an accessory to prosthetic hands for daily life activities, by providing modality-matched haptic feedback.

Keywords: Nonlinear Control, Human-Machine Systems, Robotic and Automation Systems
Abstract: Trajectory-tracking control is an important technology in the realization of automatic operations of automobiles. However, the convergence performance is heavily dependent on the velocity of the target trajectory. In this study, we propose a design method for a trajectory trading control law with preliminary defined convergence performance independent of target velocity for a target trajectory with variable velocity. Moreover, the effectiveness of the proposed method is confirmed by computer simulation.

Keywords: Nonlinear Control, Safety, Environment and Eco-Systems, Human-Machine Systems
Abstract: In recent years, an increasing number of accidents involving electric wheelchairs have been attributed to errors in human operation. To improve the safety of control systems, Nakamura et al. proposed a human assist control law using a control barrier function (CBF). The zeroing CBF (ZCBF) proposed by Ames et al. cannot consider non-autonomous systems. In this study, we propose a human-assist control law using the ZCBF for a non-autonomous system. Moreover, we implemented a ZCBF for non-autonomous system based human assist control on an electric wheelchair and confirmed the effectiveness of the proposed law through simulations and experiments.

Keywords: System Engineering, Intelligent Systems, Human-Machine Systems
Abstract: Portfolio optimization is the process of determining the best proportion of investment in different assets to maximize the profit. In the portfolio optimization problem using loan, the borrowed money can be invested in risk assets. In this paper, in order to reflect investor preferences, or values, in the portfolio with loan, the conventional formulation of the portfolio optimization problem is modified based on prospect theory. Then, in order to have an in-depth understanding of the features of the new portfolio optimization problem using loan, a fitness landscape analysis method using the convex-hull mapping is proposed. The results of the fitness landscape analysis reveal the trade-off between profits and values.

Keywords: Guidance and Flight Control
Abstract: Nowadays, unmanned aerial vehicle (UAV) is increasingly popular and being utilized for various applications. This matter is naturally accompanied by the requirement for collision avoidance and path planning functions in the presence of surrounding obstacles to ensure safety, particularly for low-altitude or indoor flights. In this paper, we propose a three-dimensional artificial potential field (APF) approach for collision avoidance and path planning purposes, and its implementation is demonstrated. For these purposes, we develop a probabilistic method using multiple Gaussian distribution functions to mimic the shape of three-dimensional obstacles, an extension of the existing two-dimensional Gaussian mixture model (GMM) approach. The parameters of the GMM are updated by the Expectation-Maximization (EM) algorithm using obstacle data that can be measured using some sensors such as 3D Lidar. To demonstrate the performance of the developed algorithms, we use a quadcopter simulation model in Matlab/Simulink environment. Future research directions of the current method are also discussed.

Keywords: Guidance and Flight Control
Abstract: In this study, we develop a trajectory following control for drones based on curvature. By considering curvature in the control law, it is possible to suppress overshoot in curved areas and improve the efficiency of the flight path compared to trajectory tracking control based only on position and velocity. To evaluate the shape of the target trajectory, curvature in the Frenet-Serre formula was used. Using the curvature, we calculated the speed of the drone on the target trajectory and devised a control system to follow it.

Keywords: Guidance and Flight Control, Adaptive and Optimal Control, Autonomous Decentralized Systems
Abstract: n this paper, the spacecraft swarm guidance and control is addressed by means of Model Predictive Control (MPC) algorithm. A novel distributed nonlinear MPC approach for formation acquisition is presented, with the purpose of minimizing data exchanged by each spacecraft, guaranteeing collision avoidance between each other and with non-collaborative obstacles. The main objective is to design a deterministic method for autonomous swarm formation acquisition around target. Providing only the target position and a distance from it, the swarm moves autonomously to the target, reaching the regular polygon shaped formation around it, and at the given distance. The main feature of the proposed algorithm is the formation adaptability to the number of spacecraft in the swarm, even considering variable-swarm. Finally, preliminary simulations are carried out for proximity operations scenario, both fixed and variable swarm formation. The method effectiveness, the independence of the results from the initial conditions, and closed-loop stability are verified by means of extensive simulations. Results makes this an interesting approach to be investigated, since it allows to not define a single reference for each spacecraft, and requires only the definition of the target position and the distance from it.

Keywords: Guidance and Flight Control, Intelligent Control
Abstract: In this study, Adversarial Inverse Reinforcement Learning (AIRL), which is a practical and scalable method to imitate the expert operations, is applied to a landing problem of aircraft. To obtain the operation model of expert pilots, we have developed a new framework based on AIRL by incorporating multimodal information. This framework allows us to build an operation model with structures similar to the human recognition systems which can infer the physical information, e.g., a distance from a current location to a runway of an airport, by using both instrument and visual information. The results of learning have demonstrated the effectiveness of our framework and successful acquisition of expert piloting skills. Furthermore, we refer to the possibility of developing education systems for pilots powered by the obtained AIRL model.

Keywords: Guidance and Flight Control, Robotic and Automation Systems, Sensors and Transducers
Abstract: This paper presents a GNSS/INS based on an error-state Kalman filter (ESKF) to combine the global navigation satellite system (GNSS) and inertial navigation system (INS) for multirotors. The onboard sensors consist of an inertial measurement unit (IMU), a magnetometer, a GNSS receiver, and a rangefinder. The proposed system can estimate the position, velocity, quaternion, and IMU bias, where the INS design significantly improves the positioning update rate of the GNSS. In addition, to execute the algorithm on flight computers with restricted computational resources, a code generator is developed to utilize the sparse and symmetric structure of the ESKF, which can produce high-efficient C code to speed up the computation time.

Keywords: Nonlinear Control, Robust Control, Guidance and Flight Control
Abstract: This paper presents a design for a trajectory generation algorithm for a sliding mode control of a quadcopter to attenuate chattering. Chattering is a well-known problem in Sliding Mode Control (SMC) that can cause high control effort and degrade the system’s performance. The proposed trajectory generation method is based on polynomial trajectories such as minimum acceleration, minimum jerk, and minimum snap, which can be used to reduce the chattering in the sliding mode control of the quadcopter. The modified SMC with tanh function is chosen for its ability to provide robust control in uncertainty and disturbance. The trajectory generation system generates smooth reference trajectories for the quadcopter to follow. At the same time, the SMC controller is used to track the generated trajectory and attenuate any chattering that may occur. Simulation results are presented to demonstrate the effectiveness of the proposed control system in achieving improved position and attitude control performance for the quadcopter.

Keywords: Adaptive and Optimal Control, Mechanical Systems Control
Abstract: A lot of research on path-planning technology for self-driving vehicles have focused on safety, time efficiency and the comfort of driving. The next needed step in the researches considering optimal behavior of vehicles is a control that takes into account the optimal behavior of the passenger. This paper considers a model predictive control method how to plan a path that restrains the passenger's behavior. We evaluate ride comfort based on passengers' motion perception characteristics.

Keywords: Intelligent Control
Abstract: Abstract: This paper presents a motion planning approach for a four-wheeled robotic wheelchair that ensures safe and comfortable movement in an unknown scenario. To address this problem, a dual quaternion-based spherical linear interpolation (SLERP) model predictive control (MPC) local path planner is developed and implemented. First, the fourwheeled robotic wheelchair is described using the unicycle model. Our approach utilizes a simultaneous localization and mapping (SLAM) method to achieve the environment in which the robotic wheelchair operates. Additionally, we use a two-layer path planner to ensures smooth and comfortable motion for the wheelchair user, enhancing their overall experience. The A* algorithm is ultilized to generate global planning path in the established grid environment. Then, an online SLERP-MPC local planner is implemented for the navigation and control of robotic wheelchairs. The simulation environment were built within the Robot Operating System (ROS). Simulation results demonstrate the effectiveness of our proposed strategy, allowing the robotic wheelchair to move safely and smoothly from its initial position to a target location. In conclusion, our work presents a validated and effective motion planning design for robotic wheelchair navigation.

Keywords: Human-Machine Systems
Abstract: This paper introduces the Safe Driving Assistance Dashcam (S-DAS). S-DAS aims to reduce traffic accidents by suppressing distracted driving and lack of peripheral awareness. Firstly, it monitors risks surrounding an ego car and gaze direction of a driver. Then it judges whether the driver is aware of them or not by comparing detected gaze direction and the location of detected risk. When the driver isn’t aware of the risk, it notifies the direction of the risk through an indicator. In order to guide driver’s gaze to the risk. The main hardware of S-DAS is equipped with double camaras (Front and Rear) which detect external environment of 360deg through ego car windscreen and driver’s face. It is connected with a smartphone which calculates risk and indicates direction of risk by Wi-fi. Finally, we introduce achievements of an actual vehicle test on a closed course.

Keywords: Intelligent Systems, Human-Machine Systems
Abstract: We introduce a language-based driver assistance system utilizing multimodal information while driving. Advanced driver assistance system, ADAS for short, is designed to prevent accidents by drivers. However, it is known that there are drivers who turn off some of the ADAS functions. Inspired by facts found in consumer survey, we focus on the problem of “annoying or excessive warnings triggers turning off of some ADAS functions” and tackle this problem using language support. We have been conducted demonstrations in simulation and real environment. We also plan to verify that our proposed method can work effectively for the feedback of risk. Based on our findings from the demonstrations, we discuss on some remaining challenges such as encouraging driver to change their behavior by themselves through language support.

Keywords: Autonomous Decentralized Systems, Relationality-Oriented Systems Design, Modeling, System Identification and Estimation
Abstract: In this paper, we propose a relative distributed controller that allows mobile sensor swarms to patrol multiple targets. The proposed relative distributed controller uses only information observed by mobile sensors without relying on communication between mobile sensors. A new objective function is employed, whose weights increase while targets are unobserved, to allow the mobile sensors to patrol the targets.

Keywords: Intelligent Systems, Intelligent Control
Abstract: This paper presents a novel framework to model the human demonstration data towards an artificial intelligence for a humanoid robot. The artificial intelligence has two sides of recognition of human behaviors and control of the robot's whole body motions. In the recognition side, the robot classifies the observation of human motion into its relevant category, and subsequently makes sentence descriptions based on semantic and syntactic knowledges. In the motion control side, the robot generates its joint angles that are kinematically similar to human demonstration with physical consistency. The proposed framework to integrate motion recognition with motion generation would be implemented into archives of human behaviors, motion retrieval, communication between human and robot.

Keywords: Adaptive and Optimal Control, Transportation Systems
Abstract: This study presents a robust optimization algorithm for automated highway merge. The merging scenario is one of the challenging scenes in automated driving, because it requires adjusting ego vehicle's speed to match other vehicles before reaching the end point. Then, we model the speed planning problem as deterministic Markov decision process. The proposed scheme is able to compute the each state value of the process and reliably derive the optimal sequence of actions. In our approach, we adopt jerk as the action of the process to prevent the sudden change of acceleration. However, since this expands the state space, we also consider ways to achieve real-time operation. We compared our scheme with a simple algorithm with the Intelligent Driver Model. We not only evaluated the scheme in a simulator environment but also conduct a real world testing.

Keywords:
Abstract: Now the automotive industry is just in the middle of a once-in-a-century paradigm shift called “CASE”. By this revolution, importance of the software increases in addition to the conventional mechanical component and the hardware. Especially to realize high performance and high reliability advanced driver assistance systems (ADAS) and autonomous driving systems (AD) importance of the software is increasing. ADAS/AD needs to understand the situation around ego vehicle and predict that it takes place next, and it is necessary to make right action plan. In this presentation I will introduce the challenge of J-QuAD to solve this technical issue by combination of the AI and the traditional control.