Keywords: Autonomous systems, Navigation, Robotics
Abstract: This article presents an obstacle avoidance framework for unmanned aerial vehicles (UAVs), with a focus on providing safe and stable local navigation in critical scenarios. The framework is based on enhanced artificial potential field (APF) concepts, and is paired with a nonlinear model predictive controller (NMPC) for complete local reactive navigation. This paper will consider a series of additions to the classical artificial potential field that addresses UAV-specific challenges, allows for smooth navigation in tightly constrained environments, and ensures safe human-robot interactions. The APF formulation is fundamentally based on using raw LiDAR pointcloud data as input to decouple the safe robot navigation problem from the reliance on any map or obstacle detection software, resulting in a very resilient and fail-safe framework that can be used as an additional safety layer for any 3D-LiDAR equipped UAV in any environment or mission scenario. We evaluate the scheme in both laboratory experiments and field trials, and also place a large emphasis on realistic scenarios for safe human-robot interactions.

Keywords: Autonomous systems, Unmanned systems, Robotics
Abstract: This paper addresses the problem of controlling a multirotor UAV with a cable-suspended load. In order to ensure the safe transportation of the load, the swinging motion, induced by the strongly coupled dynamics, has to be minimized. Specifically, using the Twin Delayed Deep Deterministic Policy Gradient (TD3) Reinforcement Learning algorithm, a policy Neural Network is trained in a model-free manner which navigates the vehicle to the desired waypoints while, simultaneously, compensating for the load oscillations. The learned policy network is incorporated into the cascaded control architecture of the autopilot by replacing the common PID position controller and, thus, communicating directly with the inner attitude one. The performance of the proposed policy is demonstrated through a comparative simulation and experimental study while using an octorotor UAV.

Keywords: Autonomous systems, Unmanned systems, Robotics
Abstract: In this paper, an Image-based Visual Servo (IBVS) Control strategy for the autonomous surveillance of coastlines using an octocopter aerial vehicle is proposed. The implemented strategy is focused on the vision-based detection and tracking of dynamic coastlines and in the presence of waves while flying in low altitudes. For this purpose, a Deep Neural Network (DNN) for the detection of the coastline is employed. The DNN is accompanied by an analytical formulation of an Extended Kalman Filter (EKF), which considers an approximate periodical wave motion model to provide an online estimate of the coastline motion directly in image space. The estimated feedback is provided to an appropriately formulated IBVS tracking controller for the autonomous guidance of the octocopter along the coastline, ensuring the latter is always kept inside the camera’s field of view. The efficacy of the proposed scheme is demonstrated via a set of comparative outdoor experiments using an octocopter flying along the coastline on various weather and beach settings.

Keywords: Autonomous systems, Guidance, Image processing
Abstract: In computer vision multiple-object detection has gain significant interest by the researchers the last decade through the evolution in the field of deep learning. Nowadays, there are many architectures achieving great accuracy in detecting multiple objects in an image. On the other hand, tracking the detecting objects remains a very difficult task and still a lot of effort is provided in that field. In general, multiple-object detection, recognition and tracking are quite desired in many domains and applications. This paper presents a target detection, tracking and localisation solution for UAVs using optical cameras. A custom object detection model, based on YOLOv4-tiny, was developed based on YOLOv4-tiny and its performance was compared against YOLOv4-tiny and YOLOv4-608. While the target track algorithm in use is base on Deep SORT, providing state of the art tracking. The presented localisation method is capable of determining the position of ground targets, detected from the custom object detection model, with great accuracy. Finally, a guidance methodology is presented, responsible for creating real-time movement commands for the UAV to follow a selected target and provide coverage over him. The overall system was tested using Software-In-The-Loop (SITL) simulation in Gazebo with up to four UAVs.

Keywords: Robotics, Autonomous systems
Abstract: Quadrotors find their roles in various sectors ranging from remote surveillance to autonomous delivery due to their capabilities of hovering, Vertical Take Off and Landing (VTOL) and rapid manoeuvring. They are a viable asset to humans in safety-critical and hazardous operations such as remote inspection and manipulation of tunnels and windmills. These applications induce external disturbances and noises along with the modelling uncertainties in the dynamics. Applications such as aerial manipulation require control from a ground station autonomously or semi-autonomously, which leads to unpredictable delays and lags. In this context, the quadrotor has to perform its goals of following the desired trajectory with minimal deviation and holding its position without any deviation while operating in the environment. So, this article analyses the existing control techniques for the quadrotor tracking problem, which also tackle parametric uncertainties, unknown time-varying delays and ensure safety.

Keywords: Unmanned systems, Modelling and simulation, Disturbance rejection
Abstract: Morphing multirotors are characterized by the capability to modify their shape during the flight, in order to negotiate narrow gaps without the need for miniaturization, thus preserving flight time and payload. In this paper, we propose a mathematical model for a morphing quadrotor characterized by telescopic arms: as extendable arms move, the center of mass position changes, as well as the inertia of the vehicle. Then, we address the tracking control problem of the telescopic quadrotor under external additive disturbances (e.g., wind), following the disturbance observer based control approach. The control scheme consists in an inner/outer loop structure, where both loops interact with a nonlinear disturbance observer. Closed loop performances are analyzed and the control scheme is validated through a realistic numerical simulation.

Keywords: Formation control, Guidance, Unmanned systems
Abstract: In this study, a guidance approach is developed for the formation flight phenomenon. This method is successful to determine any desired formation shape which is achieved by engaging in tail-chase scenarios with virtual leaders. The solution is given in two parts: kinematics of formation flight and guidance design. Impact Vector Guidance method, which is originally used to set a desired impact angle for the engagement, is modified in a way to accomplish tail-chase scenarios. The modifications on the guidance law is explained in details and their effects are given with simulation results. Lastly, an air strike is simulated using the proposed guidance law with a leader missile and its followers.

Keywords: Guidance, Nonlinear control, Unmanned systems
Abstract: An impact-angle guidance law for three-dimensional engagements is presented in this paper. The guidance law is derived without linearization, takes the cross-coupling effects into account, and does not require the time-to-go information. The approach is based on plane pursuit, which aims to bring the velocity vector of the missile into a rotating impact plane, and biased proportional navigation, in which the bias applied only over the initial part of the engagement. The proposed guidance law is in stand-alone vector form and straightforward to implement. The performance is demonstrated with simulation runs.

Keywords: Guidance, Feedback stabilization, Modelling and simulation
Abstract: Quaternion based 6-DoF tracking controllers for underwater vehicles have been described in the literature since the early 90's. However, the spread of this control concept in practical applications is very low because quaternions for describing the attitude are not so common. In this paper, a variety of mathematical properties and calculation rules for quaternion are collected and their use for the calculation of quaternion based trajectories are described. Furthermore, the use of scaling functions for the generation of different velocity-profiles (polynomial and cycloidal) is presented. The generated trajectories are tested in a simulation study for a 6-DoF tracking controller on a simple ROV model.

Keywords: Guidance, Modelling and simulation, Aerospace control
Abstract: Impact-angle control is utilized to shape the planar trajectory of a missile to obtain a desired terminal direction. When the engagement is not contained in a plane, the mechanization of a guidance law designed for this purpose will be ambiguous. There might be a number of alternative approaches to implement an impact-angle guidance law in a three-dimensional environment. This paper evaluates two of them. In the first approach, which is probably the conventional one, the pursuit angles are calculated with respect to the inertial frame and in the second, they are calculated with respect to the velocity frame. The performance of these methods is illustrated by simulations, which also include a reference impact-vector guidance law, in a comparative manner. Whereas the results imply that the one based on the velocity frame might be the better choice, both methods will enable the guidance designer to leverage two-dimensional guidance laws to shape the trajectory in three dimensions.

Keywords: Intelligent control systems, Guidance, Optimisation
Abstract: In this paper, for car-like mobile robots, a novel path planning algorithm is proposed. The algorithm is based on rapidly-exploring random trees (RRT) with fixed nodes (RRT*FN). An improvement on the RRT*FN is proposed to abide by the non-holonomic motion constraints and RRT*FN nonholonomic (RRT*FN-NH) is introduced. The new path planning algorithm handles the non-holonomic constraints as well as the constraints on the velocity and acceleration of the vehicle. The performance of the proposed algorithm RRT*FN-NH is tested on two maps obtained from Google images at three different speed profiles.

Keywords: Unmanned systems, Autonomous systems, Aerospace control
Abstract: A fire fighting aerial system is considered in this article. Such a system is comprised of a tethered hose, a high pressure water pump, and a multirotor aerial vehicle. In this paper, the overall dynamic model of this system is developed, taking into account the behavior of the hose and the recoil force of the exiting water-jet. The aerial vehicle is designed with vertical and lateral rotors, offering an additional actuation input to aid in compensation of the effects of the hose and the water-jet. A model-based controller is developed to guarantee stable flight of the aerial vehicle. A localization method is proposed, where the aerial vehicle’s relative position with respect to its base is computed by including a force sensor on the vehicle and solving the inverse of the hose curvature equations. Simulations are used to investigate the effectiveness of the overall developed model, the controller efficiency, and the accuracy of the force-based localization method.

Keywords: Robust control, Aerospace control
Abstract: In this paper, a robust path-tracking controller for a High Altitude Long Endurance (HALE) aircraft is presented. The main control paradigm for operating a HALE aircraft consists of a basic path following control, i.e. tracking a reference flight path and airspeed while dealing with very limited thrust. The priority lies in keeping airspeed inside the small flight envelope of HALE aircraft even during saturated thrust. For the basic path following objective, a mixed sensitivity approach is proposed which can easily deal with decoupled tracking and robustness requirements. To deal with saturated control inputs, an anti-windup scheme is incorporated in the control design. A novel observer-based mixed sensitivity design is used which allows directly using classical anti-windup methods based on back-calculation. The control design is verified in nonlinear simulation and compared to a classical total energy control based controller.

Keywords: Aerospace control, Nonlinear control, Nonlinear systems
Abstract: This article addresses the design of a nonlinear autopilot using Incremental Nonlinear Dynamic Inversion for a 155mm dual-spin projectile equipped with a course correction fuze. The aim of the autopilot is to control the lateral accelerations of the projectile following the embedded guidance law desired load factors to keep the projectile on the proper trajectory. Designed with a practical and straightforward methodology, a two-stage cascaded INDI structure based on time-scale separation between fast lateral rate dynamics and slow acceleration dynamics was used to linearize and control each channel. Fixed-structure robust linear controllers were designed to impose closed-loop behaviour of lateral accelerations throughout the whole flight envelope by decoupling and controlling the aerodynamic angles. Full trajectory nonlinear simulations confirms the successful implementation of the law reducing ballistic dispersion under nominal conditions.

Keywords: Aerospace control, Nonlinear control
Abstract: We consider the problem of stabilisation in predefined, finite time of the attitude of a rigid body. Inspired by classical laws in misisle guidance, the proposed control law is time-varying but smooth as opposed to classical sliding-mode-based laws that are generally discontinuous, or continuous at best, and suffer from robustness issues. Through a backstepping design, and the explicit construction of a strict Lyapunov function, we are able to ensure stabilisation to a desired attitude even in the presence of uncertainties in the inertia matrix and under the effect of additive disturbances. Numerical simulations show the efficiency of the proposed controller.

Keywords: Adaptive control, Unmanned systems, Real-time control
Abstract: This paper deals with the adaptive robust tracking control problem of a quadrotor under parametric uncertainties, actuator saturation and external wind disturbances. An adaptive robust control strategy is proposed to deal with this tracking problem. To solve the actuator saturation problem, an auxiliary system with adaptation law is considered. Global stability of the resulting closed loop system is analyzed using the sliding mode approach and the lyapunov theory. The proposed control strategy is developed to control the altitude system and attitude system representing the rotation angles in the presence of external perturbations, uncertainties and input saturation. The proposed control scheme is finally verified through various tests of simulation, also an experimental validation is carried on Parrot Mambo minidrone proving its effectiveness.

Keywords: Robotics, Autonomous systems, Image processing
Abstract: The recent advances in embedded GPU solutions allow the use of these devices for onboard mobile robotics applications. The focus of this paper is on the implementation and validation of navigation tasks for various autonomous mobile robot platforms. These platforms include ground, aerial vehicles as well as mobile manipulators. The main challenge for these implementations was the feasibility of the adopted solutions on embedded platforms with dedicated GPUs. As each of our solutions contains deep neural networks, the existence of embedded GPU is a must. We evaluated several different boards for our solutions with various experimental setups. The code and the datasets for these demos are available on the author GitHub page.

Keywords: Robotics, Autonomous systems
Abstract: This article aims to present an experimental evaluation of an offline, geometry-aware aerial visual inspection framework, specifically in constrained environment, established for geometrically fractured objects, by employing an autonomous unmanned aerial vehicle (UAV), equipped with on-board sensors. Based on a model-centric approach, the proposed inspection framework, generates inspection view-points around the geometrically fractured object, subject to the augmented static bounds to prevent collisions. The novel framework of visual inspection, presented in this article, aims to mitigate challenges arising due to the spatially-constrained environment, such as limited configuration space and collision with the object under inspection, by accounting for the geometrical information of the vehicle to be inspected. The efficacy of the proposed scheme is experimentally evaluated through large scale field trials with a mining machine.

Keywords: Robotics
Abstract: The majority of the aerial robots scientific literature investigates methods to create fully automated solutions using fixed-frame multi-rotors. However, the ability of the Micro Aerial Vehicles (MAVs) to alter their structure and adapt to various constraints posed by the environment remains unexplored. Aerial robotic platforms that can alter their shape in-flight can increase their potential value and extend the range of applications. It is essential to develop and deploy such platforms which can effectively address the missing elements for exploring previously unreachable locations. This article deals with a novel reconfigurable quadrotor whose arms are based on Soft Pneumatic Actuators (SPA) from a design, analysis, and development point of view. Simulation analysis and experimental results are provided to showcase the potential of such designs that integrate soft actuators with the traditional fixed-frame MAVs designs.

Keywords: Robotics, Autonomous systems
Abstract: This article presents an overall system architecture for multi-robot coordination in a known environment. The proposed framework is structured around a task allocation mechanism that performs unlabeled multi-robot path assignment informed by 3D path planning, while using a nonlinear model predictive control(NMPC) for each unmanned aerial vehicle (UAV) to navigate along its assigned path. More specifically, at first a risk aware 3D path planner D∗+ is applied to calculate cost between each UAV agent and each target point. Then the cost matrix related to the computed trajectories to each goal is fed into the Hungarian Algorithm that solves the assignment problem and generates the minimum total cost. NMPC is implemented to control the UAV while satisfying path following and input constraints. We evaluate the proposed architecture in Gazebo simulation framework and the result indicates UAVs are capable of approaching their assigned target whilst avoiding collisions.

Keywords: Robotics
Abstract: Edge Computing is a promising technology to provide new capabilities in technological fields that require instantaneous data processing. Researchers in areas such as machine and deep learning use extensively edge and cloud computing for their applications, mainly due to the significant computational and storage resources that they provide. Currently, Robotics is seeking to take advantage of these capabilities as well, and with the development of 5G networks, some existing limitations in the field can be overcome. In this context, it is important to know how to utilize the emerging edge architectures, what types of edge architectures and platforms exist today and which of them can and should be used based on each robotic application. In general, Edge platforms can be implemented and used differently, especially since there are several providers offering more or less the same set of services with some essential differences. Thus, this study addresses these discussions for those who work in the development of the next generation robotic systems and will help to understand the advantages and disadvantages of each edge computing architecture in order to choose wisely the right one for each application.

Keywords: Autonomous systems, Integrated control and diagnostics, Industrial automation, manufacturing
Abstract: Over the previous two decades, a tremendous impact has been created on each stage of the production value chain, through digitization of the traditional industrial processes and procedures. Since warehouses are at the heart of distributed supply chain networks, it is critical to leverage modern automation tools and through-engineering solutions to increase their efficiency and continuously meet the demanding standards. Towards this end, we describe the design of a health and safety (H&S) inspection robot capable of autonomously detecting hazard events without human intervention in ware- houses. It makes use of computer vision (CV) techniques, edge computing (EC) and artificial intelligence (AI) to identify critical occurrences that have a detrimental impact on H&S. while counting available resources using inventory tracking methodologies. Furthermore, action-based modules are acti- vated in response to the recognised event, informing warehouse workers about it and notifying other systems, operators and stakeholders, where appropriate, as foreseen by the protocol. Lastly, the conceptual architecture of the proposed autonomous robot is presented, which classifies the needed vision-based and action-based modules.

Keywords: Time-delay systems, Unmanned systems, Navigation
Abstract: This paper presents a control framework including delay estimator, state estimator, and controller to compensate for random time delays in cellular networks. The effect of network delay on the control of a quadrotor is investigated. A comparative study is done between a linear-based PD and nonlinear Backstepping controller. A time delay estimator based on the Markov stochastic model is developed. The combination of the time delay estimator and the state estimator is used to compute the control signal. Results show that the performance of both controllers in low-variation delays is approximately equivalent. According to the results, the linear-based PD controller is a good choice since it satisfies the problem conditions with a more straightforward design process.

Keywords: Autonomous systems, Guidance, Unmanned systems
Abstract: This paper presents a method for real-time path planning for fully actuated autonomous surface vehicles in confined waters. The goal is to continuously generate a collision-free path from a given initial pose to a given final pose. Both the own vehicle and static obstacles are represented as convex polygons. As soon as the environment changes, or other initial or final poses are specified, a warm start is performed, in which the results of previous solutions are reused. An optimal sampling-based approach is used to explore the search space. In a cost function, the length of the path is weighted together with the distance to all obstacles. Some parts of the cost function are calculated in advance and stored in look-up tables to reduce the computation time. The result is an optimal path from an initial pose to a final pose that avoids collisions of the vehicle with static obstacles. The proposed warm start procedure is tested by real-time experiments using different scenarios.

Keywords: Autonomous systems, Modelling and simulation
Abstract: Real-time simulators are useful tools for the development and validation of complex systems such as naval ships, aircraft or land vehicles, requiring over time more rigorous testing and integration as these systems become more and more complex. Hardware-in-the-loop simulation (HILS) is a well established technique used for a rapid and economical validation of both hardware and software sections of the developed architecture. This paper describes the design and execution of a hardware-in-the-loop simulator developed to test a maritime autonomous collision avoidance system (CAS) as well as some notable test cases to study the behaviour of the model. The HILS system is composed by a programmable logic controller (PLC) linked to two personal computers, one responsible for hosting the Linux system running the ROS Path Planner, the other for simulating the current scenario and the ship model.

Keywords: Autonomous systems, Real-time control, Robotics
Abstract: This paper addresses the three point Dubins prob- lem using a classification approach, namely by only evaluating the relative initial and final configurations with the via point position using a suitable partition of the Cartesian plane. This allows to promptly choose the path type among the eight possible thus making the path planning for three points Dubins problems much faster and more suitable for real-time applications. Some examples are provided to show the efficiency of the proposed strategy.

Keywords: Nonlinear systems, Autonomous systems, Nonlinear control
Abstract: Unlike finite time stability, wherein the upper bound of the settling-time function capturing the finite settling time behavior of the dynamical system depends on the system initial conditions, fixed time stability involves finite time stable systems for which the minimum bound of the settling-time function is guaranteed to be independent of the system initial conditions and can a priori be adjusted. In this paper, we develop several fixed time stability results for discrete autonomous systems including a fixed-time Lyapunov theorem that involves a Lyapunov difference that satisfies an exponential inequality of the Lyapunov function giving rise to a minimum bound on the settling-time function characterized by the principal and secondary branches of the Lambert W function.

Keywords: Navigation, Autonomous systems, Image processing
Abstract: Aiming to recognize familiar places through the camera measurements during a robot’s autonomous mission, visual loop-closure pipelines are developed for navigation frameworks. This is because the main objective for any simultaneous localization and mapping (SLAM) system is its consistent map generation. However, methods based on active vision tend to attract the researchers’ attention mainly due to their offered possibilities. This paper proposes a BK-tree structure for a visual loop-closure pipeline’s generated database when active vision is adopted. This way, we address the drawback of scalability in terms of timing occurring when querying the map for similar locations while high performances and the online nature of the system are maintained. The proposed method is built upon our previous work for visual place recognition, that is, the incremental bag-of-tracked-words. The proposed technique is evaluated on two publicly-available image-sequences. The one is recorded via an unmanned aerial vehicle (UAV) and selected due to its active vision characteristics, while the second is registered via a car; still, it is chosen as it is among the most extended datasets in visual loop-closure detection. Our experiments on an entry-level system show high recall scores for each evaluated environment and response time that satisfies real-time constraints.

Keywords: Navigation
Abstract: A robust navigation system is a prerequisite for a mobile robot to carry out precision agriculture tasks in modern orchards. In contrast to open fields, navigation based solely on the Global Navigation Satellite System (GNSS) is not stable in many orchards, where tree canopies may block the GNSS signal or introduce multi-path error. Research has been done to localize a robot while it travels inside a row, but navigating to the next row on the headland still relies on a reference map or artificial landmarks. In this work, we developed a row-end detection method by exploiting drastic changes in the statistical distribution of points sensed by a depth camera compared to the points inside the row. Also, a robust row entry method is implemented by building a local environment map and a reactive path tracker. The whole navigation system is tested and evaluated on a mobile robot in a vineyard. The experimental results show that the robot can detect the tree row-end accurately and maneuver a U-turn to the next row.

Keywords: Robotics, Autonomous systems, Navigation
Abstract: Autonomous navigation capability is a crucial part for deploying robots in an unknown environment. In this article a reactive local planner for autonomous and safe navigation in subterranean environment is presented. The proposed planning framework navigates the MAV forward in a tunnel such that the MAV gains more information about the environment while avoiding obstacles. The proposed planning architecture works solely based on the information of local surrounding of the MAV thus, making navigation simple yet fast. One of the biggest novelties of the article comes from solving the combined problem of autonomous navigation and obstacle avoidance. The proposed algorithm for selecting the next way point of interest also accounts in the safety margin for traversing to such way point. The approach presented in this article is also different from classical map based global planning algorithms because it favours the next way point away from obstacles in selection process and thus providing a safe path for incremental forward navigation. The approach is validated by simulating a MAV equipped with the proposed reactive local planner in order for the MAV to navigate in a subterranean cave environment.

Keywords: Robotics, Navigation, Image processing
Abstract: Robotic systems are gradually replacing human intervention in dangerous facilities to improve human safety and prevent risky situations. In this domain, our work addresses the problem of autonomous crossing narrow passages in a semi-structured (i.e., partially-known) environment. In particular, we focus on the CERN's Super Proton Synchrotron particle accelerator, where a mobile robot platform is equipped with a lightweight arm to perform measurements, inspection, and maintenance operations. The proposed approach leverages an image-based visual servoing strategy that exploits computer vision to detect and track known geometries defining narrow passage gates. The effectiveness of the proposed approach has been demonstrated in a realistic mock-up.

Keywords: Robotics, Neural networks, Navigation
Abstract: While state-of-the-art YOLO approaches have revolutionized real time object detection in mobile robotics, most of the publicly available models are trained on datasets with a small number of available classes. In addition, the difficulty in creating large datasets with many available classes for 2D object detection sets limitations to real world robotic applications and specialized use cases. This paper presents a solution that tackles these limitations by approaching object detection via fusion of 2D laser and RGB camera information resulting to a detector with 1000 learned classes. Object localization is performed in the 3D world by clustering the point cloud provided by the 2D laser scanner using the DBSCAN algorithm. The clusters are projected onto the image plane providing Regions of Interest (ROI), where proposed object bounding boxes are obtained, that are labeled with distance information. Object recognition is achieved using a pretrained, on the ImageNet dataset, ResNet and a voting schema among proposed bounding boxes, that also estimates the objects height. The detection system is used in combination with a navigation system that employs artificial potential field. The combination of the two, makes the robot’s perception easily adaptable to specialized applications and the robot’s behaviour adjustable to the complexity and variability of unstructured and unknown workspaces. The method has been implemented in ROS and tested both in simulation as well as in real case scenarios using the mobile robot Pioneer 3-DX. The work is aimed at robots with limited hardware and sensor capabilities and tries to enable detection via fusion, despite the limitations.

Keywords: Aerospace control, Modelling and simulation, Predictive control
Abstract: A collision-free formation control strategy for spacecrafts flying in formation is presented. A linear control law is developed by means of Model Predictive Control (MPC) via the dual-mode paradigm. Collision avoidance is dealt with by using Artificial Potential Functions (APFs) to keep a desired safe distance from the obstacles. The main innovation in the proposed approach is that each spacecraft independently performs the collision avoidance manoeuvres and, as a consequence, the APFs-based collision avoidance control is in charge also of the collision avoidance between spacecrafts. The optimality of the solution is discussed and numerical simulations show the effectiveness of the proposed method.

Keywords: Aerospace control, Nonlinear control, Switching systems
Abstract: This paper deals with the design of finite-time controllers for on-orbit rendezvous and capture missions. The objective is to assess the capacity of sliding–mode controllers to control a chaser spacecraft during a capture maneuver of a fleeing passive spacecraft. The control solution is based on a variable structure approach that relies on the sliding mode control theory. More precisely, the general super-twisting algorithm is used to control the chaser’s attitude, whereas the control of the relative position between the two spacecraft is based on the simplex-based sliding mode control theory. The method is tested in a full-scaled benchmark that accurately simulates the capture mission.

Keywords: Aerospace control, Robotics
Abstract: In several on-orbit applications, such as de-orbiting, continuous contact between a servicing robot (chaser) and a serviced satellite (target) is needed. The task includes chaser free-space motion and subsequent contact interaction with a floating target. To achieve this, usually grasping of the satellite is proposed. However, most of the existing satellites on orbit have no dedicated grapple fixtures. In this paper, a coordinated impedance control law is proposed for the de-orbiting of a target via continuous contact and without grasping between the chaser end-effector and the target. Since both the manipulator’s end-effector and the spacecraft base are controlled, the developed controller guarantees singularity avoidance in addition to maintaining continuous contact between the two bodies. Also, this controller is adapted to be employed in the de-spinning of a rotating satellite with known angular velocity via continuous contact. The developed control laws apply to spatial systems and are illustrated by planar examples.

Keywords: Aerospace control, Unmanned systems
Abstract: During the last decade, the efforts in space exploration have increased massively and led to a need for new ways to examine planets and other celestial bodies. The modern tendency is to create spacecraft able to scout the surface from a higher point of view, where drones have shown to be most helpful. Even if the benefits brought by this type of technology are considerable, the challenges are still difficult to overcome. This article presents a comprehensive literature review on drone technologies for planetary exploration, focusing mainly on the difficulties encountered. Considerable complications derive from the unknown environment, affecting most of the design, the mathematical model of the body, its controllability, and overall levels of autonomy. Various solutions to these challenges are proposed based on past and future missions. Furthermore, a look into the future gives an idea of possible technological developments and ways to provide the most efficient aerial exploration of other planets.

Keywords: Modelling and simulation, Aerospace control, Linear systems
Abstract: The paper focuses on developing, tuning, and testing a controller for a two-stage finless rocket during its boost phase that is based on the Linear Quadratic Regulator (LQR) optimal control method. This is accomplished by deriving and adopting a rocket simplified rigid body model that represents accurately its physical properties and the corresponding aerodynamic forces acting on the rocket system during the flight phase. The launcher is commanded through the control input thrust gimbal angle to the desired altitude using the implemented LQR-based controller. Emphasis is given to the Thrust Vector Control (TVC) system, and to the minimization of the drift caused by wind gust disturbance phenomena, which may result in a sideway motion of the rocket, and, consequently, in deviating from its desired trajectory; this is addressed, and it is overcome by considering the output parameters expressed in terms of the pitch angle, pitch rate (or angular body rate) and drift. The linearized state-space model is validated for analysis and design compensation of the pitch control logic of the ascent flight control system. The derived algorithm is, then, implemented in a Matlab/Simulink setting to demonstrate that the LQR controller provides closed-loop dynamic tracking, while the tuning of the LQR controller through the weighting matrices Q and R allows for simulating and testing how the variation of the gain directly impacts the performance of the closed-loop system and, in turn, the controller.

Keywords: Robotics, Robust control, Aerospace control
Abstract: During on-orbit tasks, when space manipulator systems (SMS) need to handle captured unknown objects accurately, robust control for compensation of uncertainties and disturbances is required. To avoid fuel consumption and/or sudden end-effector impacts with the object, the SMS is in free-floating mode, i.e., the base is not actuated. In this work, a robust Cartesian-space controller is developed for a free-floating SMS during object capture. The controller consists of a model-based part, which linearizes the dynamics globally and guarantees specific performance, and of a linear Hinf part, that assists by adding robustness in the presence of parametric uncertainties and/or disturbances. It is shown that the developed controller minimizes tracking errors and attenuates sensor noise. The sensitivity of the developed controller to uncertainties is studied by Monte Carlo simulations; the resulting tracking errors are an order of magnitude smaller than those obtained without Hinf compensation. The control method applies to spatial systems and is demonstrated by a planar example.

Keywords: Robotics, Predictive control, Optimisation
Abstract: Operation of robotic manipulators is limited to structured environments and well-defined tasks due to an offline path planning. However, flexible production processes and human-robot collaboration necessitates a real time path planning to allow for replanning a path in changing environments. In this work, we investigate established planning algorithms for their applicability to dynamic path planning problems. We further compare these methods with our approach based on model predictive control. We consider a single manipulator with six degrees of freedom in static and dynamic environments. We investigate three experimental setups and show the advantages of the proposed MPC-ELS approach over more traditional path planning algorithms in terms of several metrics, such as pathlength, execution time or trajectory smoothness. In addition, we propose a scheduling algorithm for object allocation to determine an optimal sequence for pick and place tasks with regard to minimum execution time.

Keywords: Robotics, Mechatronic systems, Industrial automation, manufacturing
Abstract: Modern collaborative and industrial robots are typically accompanied by proprietary control interfaces, which may also offer basic teaching functionality. However, many such interfaces are not suited for frequent reconfiguration of the robot system, which is essential in agile manufacturing and research. To flatten the learning curve between different interface variants and efficiently integrate external components into the process, generic robot teaching interfaces can be utilized. This paper proposes a new wearable, open-source, robot teaching interface and focuses on evaluating and comparing it with other affordable generic robot teaching interfaces in assembly task programming. Wireless input devices, including a standard keyboard, a gaming console controller, and a 6D mouse have been considered. The devices are compared in terms of perceived usability, subjective workload, and time efficiency when programming insertion tasks through a waypoint-based teaching scheme.

Keywords: Robotics, Nonlinear control, Modelling and simulation
Abstract: In this note, we propose a bounded time-varying nonnegative global tracking control law for the cable driven parallel robots (CDPR) in 3D. The goal of this control law is that the robot end-effector tracks a reference trajectory with exponential convergence. Thanks to judicious transformations of the control variables and to a particular time varying Lyapunov function we propose positive and bounded control laws guaranteeing an exponential convergence. The numerical simulations carried out show the high potential of this approach.

Keywords: Robotics, Real-time control
Abstract: Teleoperation allows robots to perform complex actions in tasks and environments where robot cognition and motion capabilities cannot support autonomy or where cooperation with humans is necessary. In this work, we present a teleoperation system for controlling the motion of a non-anthropomorphic robot arm through a natural user interface that tracks human movements through a single RGB-D visual sensor. A proportional-derivative (PD) controller is formulated to regulate robot end-effector commanded accelerations and to deal with the noisy and low-frequency human information. The system is integrated in the robot operating system (ROS) and a Universal Robots UR3 cobot is used for the evaluation. The results show that the PD controller achieves a superior performance in terms of both tracking accuracy and robot motion smoothness compared to using a proportional controller which regulates the commanded velocities. Furthermore, the same gains of the PD controller can be used to handle a wider range of human speeds. Finally, we provide real-time demonstrations of the system and the ROS pipeline.

Keywords: Multi-agent systems, Unmanned systems, Robotics
Abstract: Modern robots are used in many exploration, search and rescue applications nowadays. They are essentially coordinated by human operators and collaborate with inspection or rescue teams. Over time, robots (agents) have become more sophisticated with more autonomy, operating in complex environments. Therefore, the purpose of this paper is to present an approach for autonomous multi-agent coordination for exploring and covering unknown environments. The method we suggest combines reinforcement learning with multiple neural networks (Deep Learning) to plan the path for each agent separately and achieve collaborative behavior amongst them. Specifically, we have applied two recent techniques, namely the target neural network and the prioritized experience replay, which have been proven to stabilize and accelerate the training process. Agents should also avoid obstacles (walls, objects, etc.) throughout the exploration without prior information/knowledge about the environment; thus we use only local information available at any time instant to make the decision of each agent. Furthermore, two neural networks are used for generating actions, accompanied by an extra neural network with a switching logic that chooses one of them. The exploration of the unknown environment is conducted in a two-dimensional model (2D) using multiple agents for various maps, ranging from small to large size. Finally, the efficiency of the exploration is investigated for a different number of agents and various types of neural networks.

Keywords: Multi-agent systems, Computing and communications, Neural networks
Abstract: This paper studies the data transmission between agents of a multi-agent, deep reinforcement learning (MADRL) system (leaderless and leader-follower) using the deep Q-network (DQN) algorithm. The structure of the MADRL system consists of various clusters of agents. The agents in a cluster have the same architectures. The DQN architecture is used to present the first cluster's agents structure. The other clusters, including various architectures, are considered as the environment of the first cluster's deep reinforcement learning (DRL) agent. The goal of each static agent is to transfer data with the maximum average reward. We consider two novel observations in data transmission termed on-time and time-delay. The two proposed observations are considered when the data transmission channel is idle and the data is transmitted on-time or time-delayed. Moreover, by considering the distance between the neighboring agents, we present a novel immediate reward function by appending a distance-based reward to the previously utilized reward. We have rigorously shown which system (on-time or time-delayed) has a superior performance based on the DQN loss and team reward for the entire team of agents. The claims have been proven theoretically, and the simulation confirms theoretical findings.

Keywords: Multi-agent systems, Networked systems, Linear systems
Abstract: We consider the problems of asymptotic stability and robustness in large-scale second-order consensus networks and vehicle platoons in the discrete-time domain. First, we develop a graph-theoretic methodology to design the state feedback law for the second-order consensus networks and vehicle platoons in a discrete-time framework. We analyze the stability of such networks based on algebraic properties of the Laplacian matrices of underlying graphs and each vehicle's update cycle (also known as the time step). We further provide a necessary and sufficient condition of stability of a linear second-order consensus network in the discrete-time domain. Moreover, we evaluate the robustness of the consensus networks by employing the expected value of the steady-state dispersion of the state of the entire network, also known as squared H_2-norm, as a performance measure. We show the connection between performance measures with respect to network size, connectivity, and the update cycle. The main contribution of this work is that we provide a formal framework to quantify the relation between scaling performance measures and restrictions of the vehicles' update cycles. Specifically, we show that denser networks (i.e., networks with more communications/edges) require faster agents (i.e., smaller update cycles) to outperform or achieve the same level of robustness as sparse networks (i.e., networks with fewer communications/edges).

Keywords: Autonomous systems, Unmanned systems, Multi-agent systems
Abstract: Metropolis II aims to provide insights in what is needed to enable high-density urban air operations. It does this by investigating the foundation for U-space U3/U4 services. The final goal is to provide a unified approach for strategic deconfliction, tactical deconfliction, and dynamic capacity management. Highly-dense operations in constrained urban airspace will likely require a degree of complexity that does not exist in modern-day air traffic management. The expected high traffic demand will require a shared use of the airspace instead of assigning exclusive use of blocks of the airspace to some flights. A unified approach for traffic management is needed because at high-densities, airspace design, flight planning, and separation management become increasingly interdependent. Metropolis II builds upon the results of the first Metropolis project. Three concepts with a varying degree of centralisation will be compared using simulations. (1) The centralised concept will take a global approach for separation management. (2) The decentralised concept aims to give the individual agents separation responsibility. (3) The hybrid concept tries to combine a centralised strategic planning agent with a robust tactical separation strategy.

Keywords: Multi-agent systems, Networked systems, Optimisation
Abstract: This paper proposes a distributed dynamics that solves the least-squares problem associated with a network system of linear algebraic equations. We consider static directed multi-agent networks. Each agent in the network has access to a private subset of the linear equations. Furthermore, we assume that agents cannot acquire any information about their “out- degrees” at any time. Under the strong connectivity condition on the underlying communication network, we show that the local estimated solution of each agent converges exponentially to the exact least-squares solution of the associated network system of linear algebraic equations.

Keywords: Fault diagnosis
Abstract: This article presents a novel Auto-encoder-enabled fault resilient multi-sensor fusion architecture while incorporating an extended Kalman filter framework. The auto-encoder facilitate reconstruction of the faulty measurements from multiple onboard sensors, while the centralized extended Kalman filter enables an accurate fusion architecture. Moreover, the process is capable of successfully eliminating the additive noise appearing from the raw sensor data. The proposed method provides a robust reconstruction mechanism in the presence of time-dependent anomalies and faulty sensor measurement. The efficacy of the proposed scheme is extensively evaluated in the context of pose estimation for a micro aerial vehicle equipped with multiple onboard sensors. In addition, the evaluation process incorporates various realistic failure scenarios with artificially introduced inaccurate measurements. The superiority of the proposed Auto-encoder enabled centralized Kalman filter (AEKF) fusion is demonstrated through an extensive comparison with a recently developed Fault Resilient Optimal Information Filter (FROIF) method.

Keywords: Intelligent transportation systems, Optimisation, Multi-agent systems
Abstract: Cooperative, Connected and Automated Mobility will enable the close coordination of actions between vehicles, road users and traffic infrastructures, resulting in profound socioeconomic impacts. In this context, location and yaw angle of vehicles is considered vital for safe, secured and efficient driving. Motivated by this fact, we formulated a multimodal sensor fusion problem which provides more accurate localization and yaw information than the original sources. Simultaneously estimating location and yaw parameters of vehicles can be treated as the task of cooperative odometry or awareness. To do so, V2V communication as well as multimodal self and intervehicular measurements from various sensors are considered for the problem formulation. The solution strategy is based on the maximum likelihood criterion as well as a novel alternating gradient descent approach. To simulate realistic traffic conditions, CARLA autonomous driving simulator has been used. The detailed evaluation study has shown that each vehicle, relying only on its neighborhood, is able to accurately re-estimate both its own and neighboring states (comprised of locations and yaws), effectively realising the vision of 360◦ awareness.

Keywords: Micro and nano systems, Robotics, Mechatronic systems
Abstract: In this paper an improved implementation of a microrobotic platform, including position feedback provided by two laser sensors, and the development of a rule-based closed-loop motion controller are presented. The microrobot employs a novel driving principle, using centrifugal forces generated by two vibration motors that give the platform the ability to make motions with micrometer resolution. In this implementation, a pair of laser sensors are integrated at the bottom of the platform and calibrated through a custom procedure. The high-rate output of the laser sensors is fed to an algorithm that provides the position and orientation of the microrobot required for closed-loop motion control. Compared to using an overhead camera, this implementation, results in up to five times higher closed-loop control bandwidth, improved autonomy, and modularity. Experimental closed-loop results demonstrate the ability of the motion controller in driving the microrobot to a desired target under a microscope.

Keywords: Autonomous systems, Robotics, Hybrid systems
Abstract: This paper describes an approach to constructing control barrier functions that realize planning and control objectives that are expressed in a fragment of signal temporal logic. The particular construction is based on the navigation function method for robot motion planning and is attractive because it offers a straightforward way to design the robot control law that implements the signal temporal logic specification. The efficacy of the reported method is illustrated through simulation examples.

Keywords: Image processing, Hybrid systems, Autonomous systems
Abstract: Despite the great progress that has been done in vanishing point-based methods for road detection using visual information the results are still vulnerable to external light conditions. For that reason, the fusion of LIDAR data, alongside images can be used for a more reliable result. LIDAR data may lack illumination information but are less susceptible to light conditions. The main contribution of this paper is the use of LIDAR data to create a mask that will restrict the area of the image that could eventually be the road. More specifically, we are using LIDAR data to detect the points of the ground. By contracting an Octree, we find the best-fitting plane of each leaf and by performing clustering we estimate the ground. Next, we are mapping the points of the road to the image to create a mask for the image processing step. We extract the texture orientation using Gabor Filter and thereinafter the vanishing point. The proposed approach has been implemented and tested with over 1000 images of different road scenes in the KITTI dataset. The experimental results demonstrate that this training-free approach can detect horizon and vanishing point very accurately and robustly, while achieving promising performance.

Keywords: Marine control, Nonlinear control, Predictive control
Abstract: The trajectory tracking problem for a real-scaled fully-actuated surface vessel is addressed in this paper. A nonlinear model predictive control (NMPC) scheme was designed to track a reference trajectory, considering state and input constraints, and environmental disturbances, which were assumed to be constant over the prediction horizon. The controller was tested by performing docking maneuvers using the real-scaled research vessel from the University of Applied Sciences Konstanz at the Rhine river in Germany. A comparison between the experimental results and the simulated ones was analyzed to validate the NMPC controller.

Keywords: Marine control, Predictive control
Abstract: Due to the worldwide increase in shipping traffic, the effort put in automation of ship motion control is also increasing. Despite great success in this area during the last decades, the maneuvering of ships with azimuth drives continues to be one of the most challenging tasks in ship motion control. To tackle this challenge, this paper presents a MPC (Model Predictive Control) based concept for controlling body-fixed velocities. To do so, a mathematical model is designed to describe the dynamics of a ship in a standardized form. Thereafter, a model predictive controller to control body-fixed velocities is developed. In order to deal with non-linearities resulting from the physical properties of the ships and their actuators, especially the azimuth drives, two configurations containing different restrictions are proposed. Thus, linear MPC techniques can be applied and input constraints are explicitly taken into account. Subsequently the controller is validated with simulations of different scenarios leaned on real maneuvers. The results obtained from the simulations show, that the designed concept leads to a functioning MPC approach for controlling body-fixed velocities. They also indicate that there are still some changes that have to be applied and research that has to be done before going about a real-life implementation.

Keywords: Marine control, Predictive control, Nonlinear control
Abstract: This paper brings together the concepts of Nonlinear Model Predictive Control (NMPC) and Moving Horizon Estimation (MHE) for the adaptive control of an underactuated Unmanned Surface Vehicle (USV) equipped with two azimuth thrusters for trajectory tracking applications. The proposed methodology achieves fault detection based on the estimation of thrusters efficiencies allowing the completion of the mission in the case of single thruster failure. Simulation studies that are based on a real USV "Kerkouros" are presented to verify the effectiveness of the proposed methodology.

Keywords: System identification, Signal processing, Neural networks
Abstract: The problem of vessel roll prediction is considered in this paper within the framework of the Bayesian approach; the proposed adaptive algorithm for its solution is described. The obtained algorithm is compared with the one based on neural networks. The advantages of the proposed algorithm are discussed.

Keywords: Marine control, Modelling and simulation
Abstract: This paper focuses on the development of a parameter space model, which is applied for automatic berthing maneuvers of the German research vessel textit{DENEB} in Rostock Port. The holistic modeling approach for the entire operating range of a watercraft is characterized by a first-order structure with nonlinear parameters represented in look-up tables. The model on force level is divided in static and dynamic module, where the structure of the static part depends on the vessel specific actuator configuration. Simulation results of a highly complex hydrodynamic motion model from a ship handling simulator are used as the data basis, since such models are not directly suitable for controller design. Derived from the parameter space model, allocation and feed-forward systems are designed. Successful automatic berthing maneuvers in the port show the suitability of the model approach especially for robust maneuvering automation of vessels at low velocities.

Keywords: Robotics, Unmanned systems, Automotive control
Abstract: Human-robot shared control is used to permit an unmanned ground vehicle (UGV) to semi-automatically follow a path at a constant forward speed. The control inputs from the human and from an automatic controller are blended using a mixed-initiative blending law. A passive measure of human intent governs the blending law, permitting a rapid and smooth transition between human- and robot-control. The robot’s automatic controller is formulated using a kinematic model of the UGV, which is based on Ackermann steering. The resulting automatic control law is mathematically homogeneous. The homogeneity is used to dynamically rescale the automatic control input so that it always respects the magnitude constraints of the steering actuator. The stability of the closed-loop human-robot shared control system is proved. Illustrative simulations of the proposed control law, in which a human operator imposes steering commands on the UGV through a joystick, are presented.

Keywords: Robotics, Navigation, Autonomous systems
Abstract: Visual Simultaneous Localization and Mapping using budget-grade cameras only faces the challenges of continuous drifts that accumulate with time. While loop closure techniques mitigate the effects, they are applicable only when the robot completes a loop, which is a rarity in everyday navigation. The motion blur and smaller resolution of budget cameras further reduce the accuracy of SLAM. In this paper, we aim to solve the problem of active drift correction for a low-cost robot to solve autonomous navigation using the semantic map. Semantic maps have been used previously for re-localization but are useful only when the semantic maps themselves are highly accurate which is not realizable for budget robots. The semantic maps also face problems of correspondence matching in areas rich with recurrent semantics. To alleviate the same effects, the robot performs SLAM using a hybrid graph optimization consisting of semantic points whose pose is obtained from the semantic map database, and the non-semantic point features. The semantic map corrects for the drift, while the non-semantic features apply local smoothing that helps in mitigating the errors of the semantic map. They also apply robustness against errors in correspondence matching. The semantic graph may itself have errors, which are hence learned with time as the robot navigates. The robot adds new semantic objects into the database if it observes them, while the robot also mends the position based on the new observations. The initial semantic map is made using images captured by a camera on a few known poses, based on which it adds the observed semantics.

Keywords: Robotics, Autonomous systems
Abstract: The collision-free motion planning for mobile robots is a challenging task in dynamic environment. There are situations when the robot has no chance to select a velocity vector that would cause no collision in the next steps of the motion. Most of the motion planning algorithms for mobile robots cannot generate an appropriate solution for that problem. At the autonomous systems, the only acceptable solution in this situation is emergency braking which could cause huge damage between the robot and the obstacle. The main focus of this paper is to introduce a novel motion planning method for mobile robots that could generate a velocity vector for the robot that would cause the least damage between the robot and the environment. It can be assumed that the obstacles in the environment are passive, and low damage collisions would be attempted only when avoidance is not possible at the sampling time. If the robot has an opportunity to select a velocity vector from the Reachable Avoidance Velocities set, then a cost-function-based algorithm can be used considering different aspects.

Keywords: Robotics, Disturbance rejection, Robust control
Abstract: A legged robot needs to move in unstructured environments continuously subject to disturbances. Existing disturbance observers are not enough when significant forces act on both the center of mass and the robot's legs, and they usually employ indirect measures of the floating base's velocity. This paper presents a solution combining a momentum-based observer for the angular term and an acceleration-based observer for the translational one, employing directly measurable values from the sensors. Due to this combination, we define this observer as "hybrid," and it can detect disturbances acting on both the legged robot's center of mass and its legs. The estimation is employed in a whole-body controller. The framework is tested in simulation on a quadruped robot subject to significant disturbances, and it is compared with existing observer-based techniques.

Keywords: Robotics, Modelling and simulation, Mechatronic systems
Abstract: Planetary exploration has been affected by the ability of rovers to avoid getting trapped on sandy terrains. Currently, the European Space Agency in collaboration with the Russian Federal Space Agency are preparing the ExoMars mission, with the objective of placing a rover on the Martian surface to seek for signs of life. This rover is capable of a novel locomotion mode, commonly called wheel walking. It consists on moving the wheel forward and backward in order to improve traction and escape from terrains with a high slip ratio. The main drawback of this locomotion mode is related to the efficiency in power consumption. Therefore, it should be used only in extreme conditions. The objective of this paper is twofold. First, the definition of an experimental setup, based on a rover prototype, an experimental flat terrain and a mechanism to induce a given slip to the rover. Second, the use of this experimental scenario to validate a method, previously proposed by authors, to estimate the rover slip during the wheel walking locomotion mode.