Keywords: Multi-Robot Systems
Abstract: The typical approach to multi-robot systems is to divide the team-level tasks into suitable building blocks and have the robots solve their respective subtasks in a coordinated manner. However, by bringing together robots with different capabilities, it should be possible to arrive at completely new capabilities and skill-sets. In other words, the whole becomes greater than the sum of its parts. In this talk, we will formalize this idea through the composition of barrier functions for encoding the collaborative arrangements in terms of expanding and contracting the reachable and safe sets. Inspired by the ecological concept of a mutualism, i.e., the interaction between two or more species that benefit everyone involved, the formalism is contextualized in a long-duration setting, i.e., for robots deployed over long time scales where optimality have to take a backseat to “survivability”.

Keywords: Intelligent Control, Intelligent Systems, Adaptive and Optimal Control
Abstract: In the near future, it is expected that each person will carry a so-called artificial general intelligence (AGI) and enjoy an epoch-making, fulfilling daily life in a super-smart society. There is an active debate on how this should be realized. In this study, we envision an action intelligence that can be called a simple personal AGI that evolves autonomously and is customized as it is carried and utilized by individuals. As a framework, we focus on observer-based optimal control, and propose a system modeling that considers the situation and environment by extending the conventional system model centered on state variables, so that it can handle action control that includes situation awareness, recognition and action planning. In order to introduce it to the personal AGI that we aim for, how people deal with action planning and control is examined using a simple traffic congestion management problem.

Keywords: Intelligent Systems, Computational Intelligence
Abstract: Combinatorial optimization is an important fundamental technology, but it is challenging to find an optimal solution in a reasonable computation time. On the other hand, the excellent performance of Transformer has attracted much attention in machine learning in recent years, and its applications have been developed actively. One of them is Decision Transformer, which is an application of Transformer to reinforcement learning. This paper proposes a combinatorial optimization method using Decision Transformer. The effectiveness of the proposed method is empirically examined by applying it to the traveling salesman problem.

Keywords: Intelligent Systems, Computational Intelligence
Abstract: A deep reinforcement learning model named MineCLIP has been proposed for solving a given task in imperfect information game Minecraft by learning to associate gameplay videos corresponding to linguistic goals. The goal of the present research is to improve the success rate of the task by applying a hierarchical reinforcement learning framework to the linguistic guidance in MineCLIP, which decomposes the linguistic goal of a given task into steps. MineCLIP uses policy gradient PPO as a reinforcement learning algorithm. The proposed method uses a hierarchy of PPOs in MineCLIP to assign a single sub-policy to each language guidance, which allows step-by-step learning and facilitates task success. Using Minecraft's simulation environment, MineDojo, we confirmed that the proposed method can improve the success rate of solving tasks compared to MineCLIP.

Keywords: Intelligent Systems, Computational Intelligence, Transportation Systems
Abstract: This study explores a deep reinforcement learning (DRL) mechanism to obtain cooperative driving control of connected autonomous vehicles (CAVs) on lane-less roads. Previous studies have proposed a DRL method to learn cooperative driving control of CAVs in a simulation environment. However, the previous simulation used road tiles to construct training and testing courses, which limited the flexibility and realism of the environment. To overcome this limitation, this study creates a tile-independent course structure and proposes mechanisms for DRLs to enable learning of cooperative control without relying on the tile information. Specifically, we incorporate two new mechanisms: (i) an additional penalty based on the angle between the vehicle's direction of travel and its orientation, and (ii) utilization of information on the direction of travel 5 meters ahead. Simulation experiments were conducted to investigate the effectiveness of the proposed mechanisms, employing a roundabout environment using the tile-independent course structure. The experimental results showed that the proposed mechanisms enabled the acquisition of cooperative vehicle control, allowing vehicles to reach their destination while reducing the collision rate, even on a tile-independent course environment.

Keywords: Intelligent Systems, Mechatronics Systems, Mechanical Systems Control
Abstract: In this research, a low-cost automatic boar capture device was developed with the aim of reducing crop damage caused by wild animals, which has been increasing in recent years. The device was developed in such a way that when a boar enters in a box trap, it releases the locker system via digital signals, allowing the boar to be captured automatically. First, a highly accurate recognition algorithm for animals in a box trap was developed using the YOLO algorithm. Subsequently, the recognition algorithm was implemented on an embedded computer, installed on-site, and subjected to recognition performance experiments. In order to achieve a further cost reduction, an embedded system was developed that combined a PIR sensor using the AMB82-mini, a small microcontroller that replaces an　high cost embedded computer, and underwent operational testing.

Keywords: Intelligent Systems, Signal and/or Image Processing, Advanced Computics
Abstract: Recently, we have noted the intriguing ability of Learning Entropy (LE) with Higher-Order Neural Units (HONUs) to detect abrupt frequency changes in both sub-Nyquist signals and pure noise signals. The concept of the LE and its fundamental element, the Learning Information (LI), is revised and extended. The LI is presented as the logical counterpart of Shannon's probabilistic information and the LE as its aggregation, e.g. as an average. The approach emphasizes the computational efficiency and analyzability of HONUs with gradient learning, which implies minimal computational and energy requirements for real-time computations. For pure noise, we show that bandpass filtering and principal components improve LE performance to immediately detect frequency changes below the noise level. By demonstrating the ability of LE with linear units to detect anomalies in undersampled signals and also in pure noise, we show the potential of LE for industrial applications and perhaps also for research related to future digital communication systems or advanced analysis of data from distributed sensors in optical transmission infrastructures.

Keywords: Intelligent Systems, System Engineering, Network System Integration
Abstract: Reinforcement learning is one of the machine learning that requires a long learning time. Transition learning is a method to shorten reinforcement learning. Transfer learning is difficult to apply because the destination and source must be similar. The application method is based on empirical rules. Therefore, we propose a model that can formalize them. Several simulations are used to demonstrate the usefulness of the proposed model. The simulations are based on the classic maze problem.

Keywords: Guidance and Flight Control, Intelligent Systems, Autonomous Decentralized Systems
Abstract: Formation flight is a key feature for several new space missions concepts, and it consists of multiple spacecraft working as single rigid structure, improving flexibility and redundancy of the mission. Recent studies have shown the possibility to take advantage of Low Earth Orbit for experimental validation of new formation flight technologies. In this context, low-thrust proximity formations are investigated. The main challenge of the onboard system is to guarantee high level of autonomy, mission success and safety. Low-thrust imposes tight requirements for spacecraft relative motion. A novel approach is investigated, where each spacecraft move on a circular trajectory, defined Circular Relative Orbit, with respect to a reference orbit. Failure analysis is carried out to evaluate safety implication of tracking the proposed trajectory. A prediction model based on the presence of external disturbances is designed to improve safety distance in case of complete failure. Lyapunov Guidance Vector Field method is combined with the Artificial Potential Field, and investigated as guidance algorithm for formation flight in Circular Relative Orbit. Simulation campaign is carried out to evaluate the feasibility of the proposed approach for: formation gathering, collision avoidance, and formation reconfiguration.

Keywords: Autonomous Decentralized Systems, Rescue Systems, Networked Sensor System
Abstract: In this study, we propose a distributed search method for multiple targets in In this study, we propose a distributed search method for multiple targets in a two-dimensional space using HEDAC(Heat Equation Driven Area Coverage). HEDAC has been recently used to control multi-agent systems. In contrast to the conventional centralized HEDAC, this paper proposes a decentralized algorithm that uses probability maps to make it more practical. Specifically, each search agent shares the probability of target detection by its own search as a probability map with other agents, and is controlled along the gradient of the potential field created based on this map, enabling it to conduct its search activities in a distributed and efficient way. The contribution of this paper is to improve the flexibility of conventional search methods by decentralizing them.　Finally, we confirm the effectiveness of the proposed method through simulation validation.

Keywords: Mechanical Systems Control, Nonlinear Control, Guidance and Flight Control
Abstract: A straight-line path following and formation control problem of wheeled mobile robots is considered. Decentralized state feedback controllers that solve the problem are designed by the line-of-sight guidance algorithm and the synchronization theory. Simulation and experimental results are given to show efficiency of the proposed design of decentralized state feedback controllers.

Keywords: Autonomous Decentralized Systems, Nonlinear Control, Adaptive and Optimal Control
Abstract: 本研究では、外部に対する制御方法を検討する。 同期を誘導する。私たちは、 システム間の同期を実現するための外部入力 入力の制約の下で、 の総数に対する疎な最適制御戦略 外部制御ノードから同時に与えられたノードと 外因性インプットのサポート。その数を数値化します L0に外生的な入力を同時に適用するノードの数 ノルムと L0 ノルムの合計適用時間、および 次を使用して、問題を最適制御問題として定式化し|

Keywords: Robust Control, Multivariable Control, Guidance and Flight Control
Abstract: In this paper, the consensus properties of a linear multi-agent system are studied in the presence of a uniform delay and a directed interaction topology. The stability-switching behavior is considered, such that stability and instability of the system's modes alternate several times as the delay increases. First, the delay values causing imaginary roots of the characteristic equation are computed. The main result shows that the crossing direction of the imaginary axis is strictly related to the magnitude slope of the system's frequency response function. This result allows the depiction of a graph that contains explicitly the crossing direction information. A numerical example illustrates the effectiveness of our method applied to a consensus protocol found in the literature.

Keywords: Autonomous Decentralized Systems, Network System Integration, Intelligent Control
Abstract: We consider consensus control of a multi-agent system with transmission delays, the dynamics of which is described by a linear delay differential equation (LDDE). The transmission time delays we assume are described by a cumulative distribution function, which includes discrete and distributed time delays. Using Tutte's matrix-tree theorem, we show that the zero is a simple root of the characteristic equation derived from the LDDE if and only if the communication graph of the system has a spanning tree. Together with general linear stability theory for DDEs, we also prove the condition that the graph has a spanning tree guarantees the achievement of consensus, that is, all state variables of the LDDE converge to the same constant.

Keywords: Autonomous Decentralized Systems, Mechatronics Systems, Robotic and Automation Systems
Abstract: This paper investigates the reliability of inter-robot communication within a swarm using the Parrot AR. Drone 2.0 as a consumer Wi-Fi drone. Our study focuses on achieving collaborative swarm behavior through a centralized swarm formation involving the AR. Drone 2.0, a ground leader robot, and a ground follower robot. We analyze communication channels and programming constraints, evaluating communication reliability metrics such as data transfer rates and control cycle frequencies. The findings highlight challenges in achieving stable communication within the swarm, emphasizing the need for more open hardware and software platforms for swarm intelligence and collaboration research.

Keywords: Process Automation, Process Control, Modeling, System Identification and Estimation
Abstract: This control course is provided for operators and technical staff at production sites to intuitively understand proportional, integral, and derivative operations in PID control, which is used in the process industry to produce energy and materials. The lecture does not use difficult mathematical formulas, but rather uses a simple simulator to confirm the operation while viewing response waveforms. Students learn visually that merely increasing the control gain does not improve controllability, but that process delays and dead time can cause the response waveform to oscillate. There are also two well-known PID parameter tuning methods: the open-loop method and the closed-loop method. Both the open-loop method, in which a closed-closed loop is cut, and a step response test is performed, and the closed-loop method, in which the proportional gain is increased to create a critical oscillation, are difficult to apply to a plant in operation. In the lecture, practical PID parameter tuning methods are introduced for control engineers in the field.

Keywords: Process Control, Adaptive and Optimal Control, Nonlinear Control
Abstract: This paper presents a tunable Extremum Seeking (ES) scheme that utilizes the sign of the performance index and estimates the gradient via Recursive Least Squares (RLS) with a delay compensator. Initially, an idealized ES scheme was defined using a simple First Order Plus Dead Time (FOPDT) model with a static nonlinear function, termed NFOPDT model, by assuming complete knowledge of all model components including the gradient of the performance index. The stability of this idealized ES is analyzed by identifying the ES scheme as a Lur'e system, emphasizing the use of the gradient sign over the gradient itself would improve the stability. Then, it is shown that, if the gradient sign is used, the convergence rate of the idealized ES is nearly equal to the adaptation gain in the ES scheme, while the idealized ES induces a limit cycle whose amplitude depends on the time constant, the dead time in the NFOPDT model and the adaptation gain. These insights suggest that the convergence rate of the idealized ES can be easily controlled if the adaptation gain is set appropriately to avoid a large limit cycle. Finally, we propose to estimate the gradient using RLS and a delay compensator based on an FOPDT model to emulate the idealized ES, and show that the behavior of the proposed ES closely aligns with the idealized ES. Comparative simulation studies underscore the effectiveness of the proposed ES in terms of convergence performance, emphasizing the tunability of the adaptation gain.

Keywords: Process Control, Power Systems Control, Multivariable Control
Abstract: In this research, water level control of a spray flash desalination system is considered based on model predictive control. A water level model described by a linear time-invariant state space representation is introduced. The model contains the characteristics of valves at flash chamber outlet and after condenser outlet. Model predictive control framework is adopted to take into account the constraints on the water levels and valve openings explicitly. The effectiveness of the proposed control system was verified through numerical simulation.

Keywords: Power Systems Control, Modeling, System Identification and Estimation, Process Control
Abstract: Hot spring thermal energy conversion (STEC) is a system to generate electricity by using the temperature difference between hot spring water and normal temperature water. In this research, a simple dynamic model for a STEC plant using hybrid cycle is constructed. First, a static model is constructed based on the thermophysical properties. Secondly, the dynamics are modeled as the first order systems. To check the behavior of the constructed model, simulations were conducted.

Keywords: Power Systems Control, Modeling, System Identification and Estimation, Process Control
Abstract: This research attempts the construction of a state space model for ocean thermal energy conversion (OTEC) plant using hybrid cycle. In the model construction, a simple dynamic model for the plant is utilized. The state space model is derived by applying the linear approximation to the static calculation in the simple dynamic model. As the input and output of the model, the warm seawater flow rate and power output are considered, respectively. For the power generation control using the constructed model, proportional integral controller and linear quadratic regulator are designed. The effectiveness of the model was confirmed by simulation results.

Keywords: Power Systems Control, Network System Integration, Innovative Systems Approach for Realizing Smarter World
Abstract: Inthisstudy,weproposeamethodthatreinterpretsthedynamicsofpowersystemsthroughananalogytomass- spring-damper systems. Many textbooks on control engineering start with mass-spring-damper systems as introductory examples. The proposed analogy enables the complex power system to be perceived as a mass-spring-damper system, transforming it into a problem that is more familiar to control engineers. In many studies dealing with power systems, the generator model often used is the relatively simple constant behind-voltage model; however, this paper also employs more detailed one-axis and two-axis models, and uses analogies to compare these models. Through these mappings, we aim to build an interface that fosters the integration of knowledge between the fields of power systems and control engineering.

Keywords: Guidance and Flight Control, Autonomous Decentralized Systems, Robotic and Automation Systems
Abstract: The complexity of modern tasks necessitates the use of multi-agent systems, offering workload distribution and fault tolerance advantages. Often, fixed distances are required between these agents for their safety and coordination. Coordinated guidance strategies enable multi-agent systems to adhere to such constraints while also achieving mission-specific objectives like path following and obstacle avoidance. Developing coordinated guidance strategies tailored to specific applications presents challenges, even for two-agent systems. However, numerous guidance strategies exist for achieving these objectives in single-agent scenarios. To this end, this paper proposes a coordinated guidance strategy leveraging single-agent guidance. This guidance strategy facilitates any point between two agents to follow the desired single-agent guidance trajectory while maintaining a fixed distance between the agents, thereby enabling the two-agent system to achieve the mission objectives. The development of the coordinated strategy is shown using proportional navigation and pure pursuit guidance against a moving agent. Finally, extensive numerical simulations validate the strategy's effectiveness, demonstrating its ability to meet all objectives under realistic conditions.

Keywords: Guidance and Flight Control, Computer Aided Design
Abstract: This paper designs a fixed parameter PID controller based on previous studies. The resulting fixed parameter PID controller is applied to the nonlinear model to verify the effectiveness by changing the reference limits of the Euler angles in simulations. When the reference displacement is large, while small limits on the reference Euler angles may cause vibration and overshoot, large limits may cause the aircraft to crash. The output follows the reference value well by the appropriate limits of the reference Euler angles. Moreover, the changes in the displacement's overshoot and settling time are examined when the reference Euler angles' limits are changed from 1 degree to 90 degrees in increments of 1 degree to verify the controller's effectiveness.

Keywords: Guidance and Flight Control, Mechanical Systems Control
Abstract: In this report, an attitude control system for ultra-small satellite with magnetic torquer by permanent magnet is conducted. The authors propose a passive attitude control system for the small satellite by using magnetorquer consisted of permanent magnet 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 verify function of the constructing passive attitude control system for the small satellite, it has been given an opportunity of innovative technologies as Innovative-2 project planning by JAXA(Japan Aerospace Exploration Agency) and have been launched on November 9, 2021. Then some experiments of attitude control on polar orbit are executed, the obtained attitude data are analyzed and evaluated. As a result, it is considered that the proposing passive attitude control system with magnetic torquer using permanent magnet is effectiveness for the small satellite.

Keywords: Guidance and Flight Control, Modeling, System Identification and Estimation, Multivariable Control
Abstract: Since the maneuverability of a ship when berthing and unberthing differs depending on the speed, control design requires maneuvering motion model that reproduces the maneuverability of the target ship. In this study, a control scheme that uses a sequential estimation model to whose parameters are estimates online from observed ship motions was proposed. The proposed method was verified by simulations on a large ship to verify its estimation accuracy and control performance.

Keywords: Guidance and Flight Control, Nonlinear Control, Robotic and Automation Systems
Abstract: This paper proposes an attitude controller utilizing the sliding mode technique for a coaxial tilt-rotor unmanned aerial vehicle (CTRUAV) in the presence of external disturbances. The CTRUAV features two servos that empower two pairs of coaxial rotors to tilt independently, along with a rear rotor. This sophisticated configuration sets it apart from regular unmanned aerial vehicles (UAVs) and imposes stringent requirements on the attitude controller design. A nonsingular fast terminal sliding mode controller (NFTSMC) is designed to achieve high speed, accuracy, and robust attitude tracking performance to address these challenges. The finite-time convergence property of NFTSMC is theoretically proved, and the singularity issue is addressed. Simulations and real-time experiments are conducted to validate the effectiveness of the developed control system.

Keywords: Robotic and Automation Systems, Guidance and Flight Control, Mechatronics Systems
Abstract: Flapping wing robots have huge application potential in outdoor tasks, providing additional advantages over traditional rotary-wing aircraft. To achieve autonomous control, the flight control methodology chosen for the experiment is Proportional-Derivative (PD) Control on roll, pitch, yaw, and height control. Notably, each controller operates independently. The robotic system relies on two servo motors to control two separate wings, while the tail of the robot remains fixed. Given that the focus of this study is on small-sized robots, it is important to consider the weight of the components to minimize potential issues and ensure optimal performance. Using the Inertial Measurement Unit (IMU), the data can be transmitted from the robot’s coordinates to a computer via Bluetooth communication, facilitating real-time monitoring and control. Flight experiments are conducted within a controlled indoor environment, effectively mitigating external variables such as wind and unforeseen disturbances, thereby enabling precise analysis and refinement of the autonomous flight capabilities of the flapping wing robot. Through this research, knowledge gained from flight experimentation paved the way for the advancement of autonomous flapping wing robots in various domains, including surveillance, environmental monitoring, and search and rescue operations.

Keywords: Mechatronics Systems, Remote Sensing, Robotic and Automation Systems
Abstract: An airboat equipped with RTK-GNSS was developed to conduct sediment surveys in the dam lake and the river upstream of the dam. The airboat was equipped with pairs of ducted fans for forward and backward movement as power. Also the airboat was equipped with an precision echo sounder to measure the amount of sediment based on the distance from the water surface to the river bottom. The airboat transmits the depth measurement results while using RTK-GNSS for automatic navigation. LTE mobile phone networks were used for communication with the airboat. In areas where LTE mobile phone networks were not available, a network was established using StarLink and Wi-Fi Halow. Precise automatic navigation of the water depths resulted in accurate measurement of the riverbed profile.

Keywords: Mechatronics Systems, Robotic and Automation Systems
Abstract: Legged robots have the potential to be useful in rescue operations during disasters but their mobility is not adequate. Hydraulic and elastic actuators have been used for leg robots in the past but they have problems such as high weight and being not suitable for long-hour operation. This study aims to solve these problems by applying a variable reduction-ratio gear to robots.

Keywords: Mechatronics Systems, Robotic and Automation Systems
Abstract: In recent years, soft robot technology has gained a significant momentum with the demand for human-contact robots. TPU has flexibility, elasticity, and resilience and is suitable for robots in dynamic environments. TPU is also lightweight and has attracted much attention in the field of soft robotics. In addition, monolithic robot finger have the advantage of cost and time savings in manufacturing. In the robotic hand of the future, it will be essential for the robot not only to adapt to environments but also to have the ability to manipulate many things dexterity. In this study, we identify and analyze the dynamics of the joint while using the TPU monolithic finger and control force of fingertip using identified value. Analyzing the properties of robot finger using TPU, which is beneficial in the future, is necessary and important analytical elements for dexterous manipulation and design of soft fingers.

Keywords: Mechatronics Systems, Robotic and Automation Systems, Mechanical Systems Control
Abstract: The lunar surface is soft ground covered with sand called regolith. Lunar exploration rovers must have good traveling performance on soft ground, uneven terrain, and slopes. Crawler-type rovers have the best traveling performance on soft ground and uneven terrain. However, they have the disadvantage that traveling becomes difficult if the crawler belt is damaged. This study examines the extent to which traveling on sprockets is possible and practical when the crawler belt is damaged. We also investigate effective lugs to improve the crawler's running performance.

Keywords: Opto-Electronic Measurement, Mechanical Measurement, Ultra-High Precision Measurement
Abstract: This paper proposed an alternative method for grating period measurement based on heterodyne grating interferometry. The optical configurations for measuring the period of reflection/transmission gratings were demonstrated and 4 commercially available gratings were used to evaluate the effectiveness of the proposed method. Under precise measurement conditions, the difference in grating period between the proposed method and product specifications was less than 1%. And the grating period error was better than 1 nm.

Keywords: Robotic and Automation Systems, Mechatronics Systems, Mechanical Systems Control
Abstract: In our previous study, hybrid position/force teaching and control methods have been developed to teach desired trajectories to a robot that was integrated a parallel wire-type teaching device with a force sensor. An operator can teach the robot position and force trajectories directly and simultaneously. Subsequently, the robot was controlled to reproduce these trajectories simultaneously by a PID controller utilizing a feedback control law. In this study, teaching/reproduction experiments are conducted on complex trajectories and compared to experimental results of conventional position control method to securely confirm the effectiveness of the hybrid control method.

Keywords: Robotic and Automation Systems, Mechatronics Systems, Signal and/or Image Processing
Abstract: A method for actively changing the formation of multiple robots depending on the travelling environment is attracting attention. The control of multi-robot formation changes is planned using deep reinforcement learning. While MADDPG methods can be used for planning in known environments, re-learning may be required in unknown environments. Although model-based learning and imitation learning have been used to improve the learning time, it is unclear how to transfer the learning results of three robots to the NNs of four robots. Recently, Scaled Dot Product Attention (SDPA), which is used in natural language processing, has attracted attention for its high speed and accuracy. When transfer learning is achieved in combination with fast computation, the efficiency of edge-level re-learning is improved. In this paper, the SDPA-MAPPO algorithm is proposed. This algorithm applies SDPA to multi-robot formation learning and performs fast learning by transferring the acquired knowledge of formation changes to a certain number of robots. The proposed algorithm was verified by simulating robot formation changes and was able to achieve dramatic high-speed learning capabilities.

Keywords: Nonlinear Control, Mechatronics Systems, Robotic and Automation Systems
Abstract: In this paper, we consider the dynamic control of a platform for omnidirectional mobile robots equipped with multiple tire-mounted active caster mechanisms. We propose a generalized dynamic allocation method that addresses the overactuation problem by allocating generalized forces, consisting of two forces and one torque obtained from dynamic control laws such as backstepping control, to the actuation forces and attitude angles (i.e., steering angles) for each assembly mechanism. Through numerical simulations, we discuss the effectiveness and issues of this approach.

Keywords: Modeling, System Identification and Estimation, Mechatronics Systems, Medical and Welfare Systems
Abstract: In recent years, the use of elastic structures in robots and prosthetic legs has been attracting attention. In addition, it is desirable for practical applications such as robots to be lightweight and capable of handling large forces. Conventional bidirectional variable stiffness mechanisms cannot change stiffness separately in each direction. In contrast, a bidirectional variable stiffness mechanism using two springs has been proposed, but it imposes limitations on the design of the force points. Thus, several issues are raised. In this study, two types of springs are arranged in a double structure to solve these problems, and a mechanism that can change stiffness in both directions is developed. A prototype of this mechanism was fabricated, and experimental verification confirmed that it possesses these desirable functions. This mechanism changes stiffness not by changing the stiffness coefficient but by the amount of spring deflection. Numerical simulations were performed to analyze the behavior of the mechanism when it initially receives an impulsive external input. From the response of the kinematic model, it was confirmed that a variety of behaviors can be obtained by setting bidirectional and individual stiffnesses. The proposed mechanism is expected to be used in prosthetic devices and robots.

Keywords: Robotic and Automation Systems, Virtual Reality Systems, Human Interfaces
Abstract: In recent years, autonomous mobile robot is expected to play an active role in various fields to saving workforce. However, due to cost saving, robots in some fields are quipped with only inexpensive sensors inferior environmental recognition capability compared to expensive sensors. Then, lack of robot's environmental recognition may occur. Several studies have proposed to compensate for weaknesses in detection capability of really implemented sensors, In this study, we propose an AR (Augmented reality) system that user places virtual obstacle and adds the point clouds by virtual sensors. This paper introduces an assist function for using bird's eye view as a method for users to place virtual obstacles with better accuracy. Finally, the effectiveness of the implemented assist function is confirmed in avoiding obstacles that cannot be detected by real sensor.

Keywords: Robotic and Automation Systems, Human Interfaces, Mechatronics Systems
Abstract: In remote operations of mobile manipulators, cameras are frequently used to grasp external conditions. Remote operation of a mobile manipulator often involves simultaneous execution of multiple tasks such as moving and manipulating, and a system has been conceived to accommodate such situations by equipping multiple cameras, allowing operators to look around while operating the manipulator. However, in this case, the operator needs to manipulate the manipulator while checking multiple camera images as needed, which increases the operator's workload. Therefore, we considered reducing the burden of checking multiple camera images by presenting them as a single operation image by combining multiple camera images. In this study, we devise multiple methods of image synthesis and examine which method is effective for remote operation support based on actual operation verification and remote operation task results.

Keywords: Mechatronics Systems, Robotic and Automation Systems, Modeling, System Identification and Estimation
Abstract: Since it is very difficult for humans to perform tasks underwater, underwater robots have been actively studied in recent years. In this study, a propulsive force estimation method based on the two-point hinged oscillating wing theory is implemented and proposed for the purpose of developing an underwater robot that can perform various underwater tasks in place of humans. The proposed method is modified from the previous study in terms of the placement of the hinge points to consider a propulsive force generated by the caudal peduncle. The estimation results show that the propulsive force obtained by this method has an error with the propulsive force obtained by analysis. From this fact, the influence of the two-point hinged oscillating wing theory on the propulsive force estimation is discussed. The effect of changing the placement of the hinge points is also discussed.

Keywords: Signal and/or Image Processing, Process Automation
Abstract: In this paper, Fully Convolutional Data Description (FCDD) approach is applied to the defect detection and its concurrent visualization of industrial products. Our developed MATLAB application for building defect detection models has already allowed users to efficiently design, train and test various kinds of models such as an originally designed CNN, transfer learning-based CNN, SVM, CAE, VAE, FCN, and YOLO, however, FCDD has not been supported yet. This paper includes the software development of the MATLAB application extended to build FCDD models. The usefulness and effectiveness of a FCDD model in terms of concurrent defect detection and its visualization of understanding are compared with a conventional transfer learning-based CNN model.

Keywords: Signal and/or Image Processing, Factory Automation
Abstract: In the case that the occurrence rate of defective products is low, it is not easy to collect a sufficient amount of images including target defects for training a CNN model. As the result, it is also not easy to build a desirable CNN model for defect detection with a high generalization ability. In this paper, to cope with the need from industrial fields, a Variational Auto Encoder (VAE) modeler is implemented in a MATLAB application to systematically increase the limited number of original images. The VAE modeler is developed for users to help their design, training and test tasks for building VAE models. The VAE modeler provides users to analyze the training process based on KL loss and reconstruction loss. In our proposed training method for VAE, the two losses are separately processed and visualized. The effectiveness of the VAE modeler is evaluated through a building process of a VAE model and an image augmentation experiment including surface crack defects.

Keywords: Robotic and Automation Systems
Abstract: This article addresses the leader-following consensus problem of open multi-unmanned aerial vehicle systems (oMUAVSs) under directed communication topology. In order to achieve the leader-following consensus, the definition of leader-following consensus with respect to position and velocity is proposed for the oMUAVS, and the dynamic characteristics of the position and velocity error signals at the switching moment are characterized by using several inequalities. Then, the leader-following consensus problem is analyzed by using a distributed control protocol, and sufficient conditions are obtained for the position and velocity of UAVs to be able to converge to the position and velocity of the leader exponentially. Finally, the effectiveness of this control protocol is verified by a numerical simulation.

Keywords: Robotic and Automation Systems
Abstract: This paper presents a tip impedance controller of a two-joint robot arm. The robot arm has a joint impedance adjustment function that is achieved through the cooperative driving of the joints by six actuators possessing viscoelastic properties. We use the direct sum decomposition method to resolve the redundancy arising from driving two joints with six motors. This method enables the robot's joint impedance adjustment function to be utilized to its fullest potential while allowing for the independent design of both the motion controller and the impedance controller. The proposed controller consists of two components. The first component aims to achieve the desired tip impedance along the desired tip trajectory, and the second component intends to cancel the nonlinearity of the robot. The proposed controller does not include the position and velocity feedback. Numerical simulations demonstrate that the proposed controller can effectively implement the desired impedance properties at the end-effector.

Keywords: Robotic and Automation Systems
Abstract: Concrete structures such as bridges and tunnels are constructed on three-dimensional surfaces, and their complex environments make it difficult for robots to move. This paper describes a method for constructing stability models of floors and walls necessary for a robot to move on a three-dimensional surface. A new robot was developed based on this theory. The proposed mechanism not only uses the thrust generated by the propeller to stabilize its attitude, but also allows for efficient movement by deflecting the thrust in an appropriate direction. Based on this deflection thrust, this paper clarified the conditions under which the developed robot would not slip or fall on a three-dimensional surface, and constructed a theoretical stability model. In the experiment, we verified the robot's movement from the floor to the wall, and confirmed that the robot can move efficiently between the two surfaces.

Keywords: Robotic and Automation Systems
Abstract: For autonomous navigation, mobile robots are required to avoid obstacles ahead. We have thus far presented motion planners based on deep neural networks for obstacle avoidance. These motion planners were trained through imitation learning. However, since the robot was instructed to avoid a single obstacle, it was difficult to plan the motions for multiple obstacles. Furthermore, the motion instruction cost increases with the number of obstacles. In this paper, therefore, we focus on an open space, which is not occupied by obstacles, rather than the obstacles themselves, for motion planning. By the robot with an RGB-D camera, open-space images are fed as inputs to the motion planner. As well as the previous motion planners, the policy of the motion planner is trained for a single obstacle. Nevertheless, we show the robot based on the motion planner is able to avoid multiple obstacles through the navigation experiments.

Keywords: Robotic and Automation Systems
Abstract: This paper reports on an integration policy for heavy object handling technologies in radiation environments for the fusion device. The fusion device ITER requires a remote maintenance system using a large manipulator, which poses two significant technical challenges: limited feasible approaches due to the radiation environment and the handling of heavy objects with high precision. This study developed and combined multiple control technologies to address these challenges, such as virtual reality with structural simulator, robot vision with radiation-resistant cameras, and dual peg-in-hole operations with force feedback. In this paper, the authors propose a policy for integrating these multiple control technologies into the system. The test equipment for verification testing was designed and manufactured based on our proposed method. The achievements presented in this paper represent a significant step towards verifying technologies for handling technology of heavy objects with high precision.

Keywords: Robotic and Automation Systems
Abstract: The practical application of service robot control systems is increasingly flourishing, facing challenges in localization anomalies and obstacle perception when operating in open, large-scale environments with crowd movement and varying environmental features. Therefore, this study proposes a ROS-based mobile service robot control system and physical robot design based on the Hierarchical Extended Kalman Filter (EKF) algorithm framework and multiple sensing devices such as LiDAR and vision. The robot equipped with 2D LiDAR and vision perception fusion technology generates an enhanced localization PC-OGM (Probability Grid Occupancy Map). Through innovative improvements in mapping, localization, and navigation using 3D point cloud maps and 2D Occupancy Grid Maps (OGM), a PC-OGM is constructed. Additionally, the use of sensor fusion methods allows service robots to adapt to more complex environments and enhance their localization capabilities. This study was validated through the implementation of the designed robot in a campus restaurant, achieving the execution of meal delivery tasks in narrow corridors and complex environments.

Keywords: Robotic and Automation Systems, Mechanical Systems Control, Modeling, System Identification and Estimation
Abstract: Continuum robots have the capability to perform flexible locomotion for navigation through tortuous paths. In this paper, we propose a multi-arm robot with multiple flexible tendon-driven continuum robots with magnets to demon- strate how compliance can be used to navigate through difficult environments. Furthermore, we propose an extended mathematical model from the Cosserat rod model to solve for the inverse kinematics of the robot to use motor displace- ments as inputs for robot control. We show an initial prototype of our system, and demonstrate the proposed robot’s movement with an obstacle avoidance and an u-shaped locomotion experiment

Keywords: Adaptive and Optimal Control, Guidance and Flight Control, Autonomous Decentralized Systems
Abstract: As satellites have become smaller, there are growing expectations for coordinating multiple small satellites in space missions. However, small satellites are limited in the performance of the software and communication modules that they can load in terms of their size, weight, and cost. Therefore, it is necessary to reduce the communication resources required for control. In addition, packet loss is expected to occur due to low performance of the communication module, solar flares, cyber attacks, and other factors. Motivated by these facts, this paper deals with cooperative control of multi-agent systems in the presence of communication capacity constraints and packet loss in inter-agent communication. The basis of the proposed method is a hierarchical optimal control law consisting of individual feedback and cooperative feedback, of which the cooperative feedback is modified. Specifically, an observer and a quantizer are incorporated and estimation by an observer is used to compensate for the information loss due to quantization and packet loss. Additionally, the relationship between the probability of packet loss and the required data rate is clarified. Numerical simulations of satellite formation control confirm the effectiveness of the proposed method and the validity of the derived conditions.

Keywords: Adaptive and Optimal Control, Mechatronics Systems, Flow Measurement and Control
Abstract: This research deals with cooperative wind disturbance estimation using multiple drones. Meteorological phenomena within approximately 100 meters above ground level is highly influenced by the ground surface and closely related to the wind patterns. For a better prediction of such phenomena, the acquisition of wind information is crucial. Among various tools to obtain wind information, the use of drones is a promising method due to their advantages in mobility and cost. The obtained wind information is also useful for motion control of drones. Furthermore, if wind disturbance estimation can be achieved by multiple drones, it is expected to improve estimation performance and provide redundancy compared to single-drone systems. Our research group has developed a cooperative wind disturbance estimation method employing the notion of optimal control and adaptive control. The effectiveness of this method has been confirmed through numerical simulations but had not been validated in experiments until recently. This presentation is intended to give an experimental validation of the effectiveness of our method for cooperative wind disturbances estimation.

Keywords: Autonomous Decentralized Systems, Adaptive and Optimal Control
Abstract: Centipedes generate waves in their legs that propagate from anterior to posterior in an antiphase manner between the left and right sides. Our preliminary observations have indicated a tendency to adopt an in-phase gait on sandy substrates. This is also observed when the centipedes ascend branches, where the elongation and contraction of body segments contribute to propulsion, a mechanism distinct from that on the sandy substrates. This study, therefore, analyzes the gait of centipedes on soft terrain to elucidate changes in gaits and aims to develop a robot capable of altering its gait on both rigid and soft terrains. The robot was designed to replicate the ganglia and chain-like structures of the centipede nervous system, enabling active leg movement and the detection of leg postures via bending sensors. The findings confirmed that the centipedes transition from the antiphase to the in-phase gait on the sandy substrates, thereby increasing the duration of the propulsive phase. This transition would be attributed to the legs engaging the ground longer to gain propulsion on the soft terrain. Additionally, the prototype demonstrated the ability to discern the ground rigidity.

Keywords: Guidance and Flight Control
Abstract: This study considers a minimum-configuration, compact and simple lander that does not have the 6-DOF controllability and precise guidance laws that conventional planetary landers usually have. While conventional planetary landers are high-performance, high-precision and high-redundancy systems, which naturally leads to low mission frequency, a small lander with a minimal configuration and moderate precision can realize a high-risk, high-return but high-mission-frequency landing system. This is expected to open the door to planetary landing missions on a wider range of terrestrial celestial bodies that have been difficult to plan for in the past. The lander proposed in this study has two solid rocket motors with constant thrust for the propulsion system, which is small, simple, and cost-effective. Two solid rocket motors are mounted on gimbals to change the thrust vector symmetrically. The lander is spin stabilized, and its vertical position and velocity are controlled by controlling gimbals actuated only by one actuator. In this study, the basic feasibility of the proposed lander is verified through simulated experiments using drone technology in a ground environment. A solid rocket motor is simulated with a fixed-speed electric motor, and after numerical experiments under this environment conditions, simulated experiments are conducted to maintain a rotating drone at a constant target altitude on the ground.

Keywords: Guidance and Flight Control, Adaptive and Optimal Control
Abstract: We propose a control method for quadcopter drones using Ultra-Wideband (UWB) ranging and Angle of Arrival (AoA) measurements, and present the results of experiments conducted with actual equipment. In disaster situations or indoor environments, location systems, such as motion capture systems or global-navigation satellite systems (GNSS), may be unavailable. In this study, we aim to achieve autonomous flight of quadcopters in non-GNSS environments. We use UWB tags that can measure both the distance and angle of arrival from the initiator to determine the relative position of the quadcopter. By combining UWB with inertial measurement unit (IMU), we estimate the state of the quadcopter. We conduct experiments on a micro drone, which is less than 100 grams, and evaluate the performance.

Keywords: Intelligent Control, Mechanical Systems Control
Abstract: In order to realize the safe cooperative work between a human-operated hydraulic excavator (HEx)and an autonomous excavator (AEx), the motion planning of the AEx must take into account the behavior uncertainty of the HEx. A motion planning method for autonomous excavators is proposed that uses motion prediction results including the uncertainties. The prediction is performed using a Gaussian process regression model created using operational data. In addition, the motion planning of the AEx is devised by a real-coded genetic algorithm. Then the collision-free cooperative work can be achieved by the proposed method taking uncertainty into consideration. The effectiveness of the proposed method is verified by a numerical simulation.

Keywords: Mechanical Systems Control
Abstract: This study discusses a practical implementation of resilient consensus for mobile robots based on recently developed Mean Subsequence Reduced (MSR) algorithms. In a multi-agent system consisting of mobile robots, each robot agent exchanges information, such as its position, with the neighboring agents and decides to move the robot’s body. This study considers a situation where malicious robot agents partially emit abnormal information due to failures or cyber-attacks. The normal agents update their states using information from neighboring agents based on a predetermined control rule. In contrast, the malicious agents update arbitrarily, affecting the entire system and threatening the consensus. This study introduces MSR algorithms, known as resilient consensus methods, that suppress the influence of malicious agents. For the mobile robots on the plane, this study separates a multi-robot system into two multi-agent systems of each coordinate. This study starts with a setting in which the malicious agents of both coordinates coincide. Since a simple consensus of the robots stacks the bodies around the consensus point, this study introduces the virtual structure to shape the formation of the mobile robots.

Keywords: Mechanical Systems Control, Multivariable Control
Abstract: Torque-unit Manipulator (TUM) is a new type of space manipulator that does not incorporate motors within its joints but instead uses torque-units composed of a disc and motor on each link. The links of TUM can be controlled by conventional control laws, but they encounter residual angular velocities in the discs after control. This study aims to discover motion trajectories that simultaneously reduce the residual angular velocities in the discs to zero as the links reach their target positions. We conduct this exploration through motion simulations of TUM in which we systematically vary the values of free parameters, which are the coefficients of a sixth-order polynomial time function for trajectories. Our goal is to find combinations of coefficients that minimize both the residual angular velocities and the integral norm of the difference between the fifth-order polynomial trajectories, which are unique and smooth by giving a final and initial positions, and the generated sixth-order polynomial trajectories. Upon identifying optimal sets of coefficients, we update and retain the values of these optimal sets and their corresponding norm values. We visualize them on a 3D graph, thereby enhancing data analysis.

Keywords: Mechanical Systems Control, Signal and/or Image Processing, Robotic and Automation Systems
Abstract: Considering the global labor shortage, the automation of order picking, one of the main tasks in logistics warehouse, is advancing to reduce physical burdens. However, many automation systems can only pick and hold drawers with mechanically constrained movements and cannot place them back into shelves after holding. Therefore, in this study, we developed a robotic hand and a dedicated drawer that allow the robot to hold and store the drawer after picking it up. Additionally, since drawers are used in various environments, precise positioning of the hand without using positioning jigs is necessary. This study focuses on visual servoing technology for this positioning task. However, conventional visual servoing technologies struggle to achieve high-precision positioning for drawers with insufficient texture. To address this, we propose a method using active visual servoing that projects theoretically derived pattern light onto the object for drawer picking and storing. As a result, we confirmed higher positioning accuracy and a higher success rate of picking and storing compared to conventional visual servoing methods.

Keywords: Multivariable Control, Modeling, System Identification and Estimation, Nonlinear Control
Abstract: In this research, a discretization method for fractional-order systems given in the state-space representation is studied. It is derived based on matrix Mittag-Leffler functions, which are used to present the solution of the state equation of the fractional-order systems. This method has two advantages; (1) its discretization is strict presentation, i.e. is not an approximation such as the CRONE-based fractional treatment, (2) it takes the time evolution of the fractional-order systems like linear discretized systems. Some numerical verifications are given to demonstrate the proposed method.

Keywords: Nonlinear Control, Guidance and Flight Control
Abstract: Spacecraft formation flying (FF) is an innovative technology that breaks through the physical constraints of the size of a single spacecraft. Space interferometer missions are being considered as applications of FF, which require precise control of the relative positions between spacecraft. In such missions, micro-thrusters mounted on spacecraft can precisely output commanded thrust, but the maximum thrust is severely limited. Nonlinear control of the port-Hamiltonian system is reasonable for precise FF. It can control efficiently based on the mechanical structure, which leads to longer mission life. Therefore, the relative orbital motion of spacecraft is represented by port-Hamiltonian systems, and an error system for a given reference trajectory is constructed. Then, a variable gain controller is designed to consider the effect of actuator saturation due to micro-thrusters. Previous studies have used constant gain controllers. Although a larger gain provides better tracking performance, the upper limit of the stabilizable error becomes smaller in the presence of input saturation, and vice versa. Therefore, this paper proposes a variable gain mechanism in which the gain increases near the reference trajectory and decreases far away from the reference trajectory to solve the trade-off between stability and tracking performance. Then, the variable gains are optimized under the derived stability conditions.

Keywords: Nonlinear Control, Modeling, System Identification and Estimation
Abstract: In recent years, nuclear fusion power generation has garnered significant attention as a promising solution to the global energy crisis. This technology leverages nuclear fusion reactions, primarily utilizing fuel derived from seawater, making it an attractive option worldwide. Fusion reactions occur at extremely high temperatures, transitioning matter to a plasma state, which is the fourth state of matter beyond solid, liquid, and gas. Plasma interacts with electric and magnetic fields, and its dynamics are governed such as by MagnetoHydroDynamic (MHD) phenomena. Due to its electromagnetic fluid properties, plasma inherently exhibits instabilities known as MHD instabilities, which have posed a major obstacle to the realization of nuclear fusion power. Thus, controlling these instabilities is a critical research challenge. Our research employs a control approach utilizing port-Hamiltonian systems, which naturally incorporate energy conservation laws and physical constraints. This framework facilitates efficient modeling and suppression of the complex behavior of plasma dynamics. Specifically, we utilize control through interconnection based on Casimir functions, which are system invariants. By adopting port-Hamiltonian systems, we aim to develop effective strategies for controlling MHD instabilities and advance the feasibility of nuclear fusion power generation.

Keywords: Nonlinear Control, Robotic and Automation Systems
Abstract: This poster focuses on model predictive control (MPC) for a hexacopter with linearization techniques. The hexacopter has six tilt rotors, and a particular gear train enables the rotors to tilt simultaneously. Since a single motor can tilt all the rotors, one can reduce the weight of the hexacopter’s body. In general, titling makes moving fast and hovering on slopes to do various tasks possible. For such an attractive vehicle, MPC is a choice to impose constraints on the rotor speeds and attitude angles. However, the tilt strengthens the nonlinear characteristics and deteriorates the control performance. Nonlinear MPC methods often require solvers for nonlinear programming, which is difficult to implement on onboard computers due to the computational burden. Thus, this poster avails linearization techniques with MPC. This poster discusses the model predictive controllers based on first-order approximation and exact linearization, respectively, and compares them through numerical experiments. Moreover, this poster considers instant MPC instead of conventional MPC for linear systems to reduce the sampling period.

Keywords: Nonlinear Control, Robust Control
Abstract: This study proposes an orbit deployment control method using low-thrust propulsion for the satellite constellation deployment. The previously proposed Lyapunov-based nonlinear control method assumes that disturbances are known. However, in the real environment, disturbances are unknown. Therefore, in this study, sliding mode control which is more robust for unknown disturbances is used. First, the orbit dynamics are modeled with modified equinoctial elements. Then, orbit requirements are formulated as the sliding mode surface, and a first-order sliding mode controller is constructed. However, since thrusters have an upper limit of the output, input saturation must be considered in the control. In ordinary first-order sliding-mode control, orbit control considering the input saturation sometimes cannot be achieved. Therefore, this study incorporates a variable gain in the controller. This enables efficient control with low fuel consumption and helps achieve precise and robust orbit control even when input saturation is taken into account.

Keywords: Nonlinear Control, Transportation Systems, Mechanical Systems Control
Abstract: Improving automobile fuel efficiency has become an important issue in the efforts to prevent global warming. Various technologies, such as engine downsizing, reducing the number of cylinders, and cylinder deactivation, are actively being researched to achieve this goal. However, reducing the number of engine cylinders can lead to increased engine torque fluctuations, resulting in higher torsional vibration in automobile drive systems. In this study, we focused on a device that can provide auxiliary torque to the drive-train, which reduces torsional vibration in the automobile drive system. Then we proposed a command shaping method that shapes the reference of the auxiliary torque to reduce torsional vibration. Finally, we confirmed the effectiveness of the proposed method through simulation and bench test.

Keywords: Power Systems Control, Relationality-Oriented Systems Design
Abstract: This study considers the supply-demand balance of electricity when PV power generation and large storage batteries are widely used and assumes that multiple thermal power generators and multiple storage batteries will be used in a day-ahead operation plan that can meet the net demand. In the previous studies, the model was based on a day-ahead operation plan within a single region. However, we assume a model in which similar settings are considered within multiple regions, and power is sent between regions to build a power network. The problem here is the amount of PV power is difficult to predict, which causes uncertainty in the net demand prediction. Therefore, the net demand prediction is given not as a single prediction but as an interval prediction, and the optimal power generation plan is considered in the sense that the economic cost is minimized no matter what the demand becomes on that day within that interval. The main purpose of this research is to accurately determine the optimal adjustment range of the four parameters (the power generation by thermal power units, the rate of charge/discharge power of storage batteries, the capacity of storage batteries, and the transmission power between power networks).

Keywords: Robotic and Automation Systems, Remote Sensing, Guidance and Flight Control
Abstract: We are developing a tilting-frame multi-rotor UAV that can change the pitch angle of the airframe while keeping the UAV‘s�@propeller horizontal, working in high and dangerous places that are out of reach. The tilting frame multi rotor UAV is fitted with a work arm for inspecting high, sloping, and curved wall surfaces. In this study, we developed a system to measure the angle of the wall surface to the work arm using four TOF distance sensors mounted on the connection between the work arm and the fuselage. In some cases, the angle of the wall could be estimated accurately, but in other cases there was a large error of around 10 degree. We also evaluated the distance measurement characteristics of the TOF sensor using targets made of different materials and with different orientations.

Keywords: Robotic and Automation Systems, Sensors and Transducers, Mechanical Systems Control
Abstract: We have been developed an autonomous motion control of mobile robot using segmentation method. Conventional systems can run straight ahead without markers for straight routes, but to turn left or right on a corner, it is necessary to recognize the markers and turn. To solve this problem, the proposed system changes its course by recognizing corner paths without using markers, thus enabling the mobile robot to move arbitrarily. In this system, inputs from the camera are segmented using deep learning to recognize the floor and wall, and based on the results of the floor recognition, the shape of the path is determined. Autonomous motion within a corridor is performed by specifying speed commands in the direction of travel. The effectiveness of the proposed system is examined through practical experiments.

Keywords: Robust Control, Autonomous Decentralized Systems, Sensors and Transducers
Abstract: This study proposes a method for integrating Scan Matching, RTK-GNSS/IMU, and DR position estimation methods to account for real-time errors in position estimation. For autonomous driving, position estimation methods such as Scan Matching using three-dimensional point cloud maps and LiDAR, RTK-GNSS/IMU using satellite positioning and an IMU, and DR using wheel speed sensors and an IMU are widely used. However, these methods are known to suffer from degraded estimation accuracy depending on the environment. Previous research has proposed multi-sensor positioning that adopts the optimal method for each environment, achieving environment-independent position estimation. However, since the optimal position estimation results are set based on prior evaluation, the issue of not considering real-time position estimation errors remains. In this study, we integrate Scan Matching, RTK-GNSS/IMU, and DR position estimation methods to develop a position estimation method that can account for real-time errors[1] and is robust to varying environments. The results of the proposed method show that by integrating these position estimation methods, it is possible to compensate for locations where the estimation accuracy of each method deteriorates and achieve high-accuracy position estimation suitable for autonomous driving. [1]K. Aoki, et al.: “Error covariance estimation of 3d point cloud registration considering surrounding environment”, Journal of Robotics and Mechatronics.

Keywords: Robust Control, Modeling, System Identification and Estimation, Mechanical Systems Control
Abstract: For robust feedback controller synthesis, a main issue is to reduce conservativeness of the system by making use of information on the physical model. Flexible structures have weakly damped vibration modes as well as poles at origin, and it is expected to benefit from modeling via coprime factorization of the transfer function. In this presentation, we discuss an approach that utilizes gap metric with a phase compensator design for a certain robust stability margin, which is for position tracking and vibration suppression, based on a rigorous beam model with velocity input. The effectiveness of the proposed approach is demonstrated through numerical simulations and control experiments, based on frequency response data.

Keywords: Signal and/or Image Processing, Intelligent Control, Agricultural and Bio-Systems
Abstract: Automation application on crops harvesting has increased in the past decades. Various types of harvesting robots are emerging in both commercial and research areas. One of the main challenges is the precision alignment for the gripper and the target crop. An undesired dislocation can do harm to both gripper and crop. This issue is mainly caused by the uncertainties from the manipulator such as length and angle. By solving this problem, a self-built robot system with dual-camera setup is implemented. The perception of the tomato is done by a fixed depth camera and the dislocation error is measured by the camera on the gripper. The proposed IBVS (Image-Based Visual Servoing) controller is designed to deal with the given error feedback and the proof of asymptotically convergence is provided. Furthermore, the error compensation reduces the time for harvesting process. The experiments are done in the lab and greenhouse, and tested under several conditions.

Keywords: Identification and Estimation, Human-Machine Systems, Modeling, System Identification and Estimation
Abstract: Although the evaluation of standing balance has been used to diagnose the decline in disease and assess the degree of recovery in rehabilitation, a reliable method has not been established. The purpose of this study was to model the response of the human body to the horizontal sway of the support surface and evaluate the stability of the identified balance parameters of each subject. For the balance control law, control over the horizontal oscillation of the support surface was assumed in addition to the center of mass feedback control with delay. Frequency analysis was applied to the estimated center of mass displacement based on force sensor measurements to identify the individual balance characteristics in the assumed balance control model. A stability index was introduced with the optimal value corresponding to the condition with the fastest convergence in terms of control engineering. The reproducibility of the identified control parameters and stability index was confirmed by the intraclass correlation coefficient of the results obtained during the 3-day test. Parameters representing the basic elements of balance control were sufficiently reproducible; however, parameters corresponding to horizontal perturbations of the support surface were less reproducible. The stability indices were sufficiently reproducible.

Keywords: Modeling, System Identification and Estimation
Abstract: To achieve efficient control, it is necessary to construct an accurate mathematical model. Therefore, in recent years, there has been active research on system modeling using deep learning models. In particular, deep learning models incorporating state-space models (deep state-space models) can capture long-term dependencies and non-linearities in data. However, as the number of parameters in deep models increases, it becomes challenging to use the trained deep models on devices with limited computational resources. Thus, this study proposes a method for parameter reduction in deep state-space models through model order reduction theory. Specifically, we address this issue by developing an H2 model order reduction method for complex diagonal state-space models appearing within deep models.

Keywords: Modeling, System Identification and Estimation, Discrete Event Systems, Social Systems
Abstract: Industrial control systems play an important role in society's infrastructure and must be available and protected. In control systems, redundant controllers have been adopted by many companies as a countermeasure against hardware failures. Redundant controllers have more information than single controllers. During eavesdropping, which is the initial stage of a cyber-attack, the internal structure of the redundancy can be identified from the partial information of the system. Therefore, this study aims to enable a quantitative evaluation of the possibility of identifying the internal structure of a system in a situation where a part of the system has been compromised. The analysis makes use of the ‘opacity’ of the discrete event system theory, which defines a system as secure if the leaked information and the secret information have nothing in common. Specifically, the current state set of the system is defined as the secret information and the maximum estimation region is derived from the leakage information and the Petri net property ‘P-invariant’.

Keywords: Modeling, System Identification and Estimation, Intelligent Systems
Abstract: In the construction industry, the number of workers has been declining due to the declining birth rate and aging population, and labor shortages cause productivity to decline. To improve productivity in the construction field, keeping work machines in operation is important. Specifically, machine breakdowns should be predicted in advance, and maintenance activities should be conducted. If the load applied to a machine in operation is known, breakdowns can be predicted based on the condition of the load. However, the load applied to construction machinery, such as hydraulic excavators, varies depending on the work situation and environment. Therefore, it is necessary to construct a load estimation model corresponding to these conditions. This study proposes a new load estimation modeling method based on database-driven modeling. This approach utilizes machine learning to firstly identify the operation of construction machinery and followed by the generation of local models corresponding to these operations using a database. The experiment results using a remote-controlled excavator demonstrate that highly accurate load estimation is achievable regardless of the operation in applying the proposed method.

Keywords: Modeling, System Identification and Estimation, Medical and Welfare Systems
Abstract: Compared to the standing posture, the center of mass (COM) is easier to control in the sitting posture because the base of support is wider. On the other hand, because the vibration of the seat surface is easily transmitted to the head, the importance of COM control in balance control is thought to decrease and head acceleration control increases. Although system identification through a model is desirable for this verification, but previous studies on standing have focused only on COM control and excluded the head acceleration control from the system. This study aims to evaluate the weighting of COM control and head acceleration control through the identification of sitting balance system. The responses of 10 healthy male subjects in their 20s to seat rocking at frequencies of 0.05 to 1.5Hz were measured using force platforms under the buttocks and feet, and a head acceleration sensor. The addition of the head acceleration component to the feedback control law facilitated the reproduction of the frequency response diagram. It is hoped that this method can be applied to vestibular sensory testing by identifying the balance system in the sitting posture.