A Nonlinear Model Predictive Control Scheme for Cooperative Manipulation with Singularity and Collision Avoidance

This paper addresses the problem of cooperative transportation of an object rigidly grasped by $N$ robotic agents. In particular, we propose a Nonlinear Model Predictive Control (NMPC) scheme that guarantees the navigation of the object to a desired pose in a bounded workspace with obstacles, while complying with certain input saturations of the agents. Moreover, the proposed methodology ensures that the agents do not collide with each other or with the workspace obstacles as well as that they do not pass through singular configurations. The feasibility and convergence analysis of the NMPC are explicitly provided. Finally, simulation results illustrate the validity and efficiency of the proposed method.Comment: Simulation results with 3 agents adde

Decentralized Abstractions and Timed Constrained Planning of a General Class of Coupled Multi-Agent Systems

This paper presents a fully automated procedure for controller synthesis for a general class of multi-agent systems under coupling constraints. Each agent is modeled with dynamics consisting of two terms: the first one models the coupling constraints and the other one is an additional bounded control input. We aim to design these inputs so that each agent meets an individual high-level specification given as a Metric Interval Temporal Logic (MITL). Furthermore, the connectivity of the initially connected agents, is required to be maintained. First, assuming a polyhedral partition of the workspace, a novel decentralized abstraction that provides controllers for each agent that guarantee the transition between different regions is designed. The controllers are the solution of a Robust Optimal Control Problem (ROCP) for each agent. Second, by utilizing techniques from formal verification, an algorithm that computes the individual runs which provably satisfy the high-level tasks is provided. Finally, simulation results conducted in MATLAB environment verify the performance of the proposed framework

A Robust Model Predictive Control Approach for Autonomous Underwater Vehicles Operating in a Constrained workspace

This paper presents a novel Nonlinear Model Predictive Control (NMPC) scheme for underwater robotic vehicles operating in a constrained workspace including static obstacles. The purpose of the controller is to guide the vehicle towards specific way points. Various limitations such as: obstacles, workspace boundary, thruster saturation and predefined desired upper bound of the vehicle velocity are captured as state and input constraints and are guaranteed during the control design. The proposed scheme incorporates the full dynamics of the vehicle in which the ocean currents are also involved. Hence, the control inputs calculated by the proposed scheme are formulated in a way that the vehicle will exploit the ocean currents, when these are in favor of the way-point tracking mission which results in reduced energy consumption by the thrusters. The performance of the proposed control strategy is experimentally verified using a $4$ Degrees of Freedom (DoF) underwater robotic vehicle inside a constrained test tank with obstacles.Comment: IEEE International Conference on Robotics and Automation (ICRA-2018), Accepte

Cooperative and Interaction Control for Underwater Robotic Vehicles

In this dissertation we address the problem of robust control for underwater robotic vehicles under resource constraints and inspired by practical applications in the field of marine robotics. By the term “resource constraints” we refer to systems with constraints on communication, sensing and energy resources. Within this context, the ultimate objective of this dissertation lies in the development and implementation of efficient control strategies for autonomous single and multiple underwater robotic systems considering significant issues such as: external disturbances, limited power resources, strict communication constraints along with underwater sensing and localization issues. Specifically, we focused on cooperative and interaction control methodologies for single and multiple Underwater Vehicle Manipulator Systems (UVMSs) considering the aforementioned issues and limitations, a topic of utmost challenging area of marine robotics. More precisely, the contributions of this thesis lie in the scope of three topics: i) Motion Control, ii) Visual servoing and iii) Interaction&amp;Cooperative Transportation. In the first part, we formulated in a generic way the problem of Autonomous Underwater Vehicle (AUV) motion operating in a constrained environment including obstacles. Various constraints such as: obstacles, workspace boundaries, thruster saturation, system‘s sensing range and predefined upper bound of the vehicle velocity are considered during the control design. Moreover, the controller has been designed in a way that the vehicle exploits the ocean currents, which results in reduced energy consumption by the thrusters and consequently increases significantly the autonomy of the system. In the second part of the thesis, we have formulated a number of novel visual servoing control strategies in order to stabilize the robot (or robot’s end-effector) close to the point of interest considering significant issues such as: camera Field of View (FoV), Camera Calibration uncertainties and the resolution of visual tracking algorithm. In the third part of the thesis, regarding the interaction task, we present a robust interaction control scheme for a UVMS in contact with the environment, with great applications in underwater robotics (e.g. sampling of the sea organisms, underwater welding, object handling). The proposed control scheme does not required any a priori knowledge of the UVMS dynamical parameters or the stiffness model. It guarantees a predefined behavior in terms of desired overshoot, transient and steady state response and it is robust with respect to external disturbances and measurement noises. Moreover, we have addressed the problem of cooperative object transportation for a team of UVMSs in a constrained workspace involving static obstacles. First, for case when the robots are equipped with appropriate force/torque sensors at its end effector we have proposed a decentralized impedance control scheme with the coordination relying solely on implicit communication arising from the physical interaction of the robots with the commonly grasped object. Second, for case when the robots are not equipped with force/torque sensor at it end effector, we have proposed a decentralized predictive control approach which takes into account constraints that emanate from control input saturation as well kinematic and representation singularities. Finally, numerical simulations performed in MATLAB and ROS environments, along with extensive real-time experiments conducted with available Control Systems Lab (CSL) robotic equipment, demonstrate and verify the effectiveness of the claimed results.QC 20190514</p

Cooperative and Interaction Control for Underwater Robotic Vehicles

In this dissertation we address the problem of robust control for underwater robotic vehicles under resource constraints and inspired by practical applications in the field of marine robotics. By the term “resource constraints” we refer to systems with constraints on communication, sensing and energy resources. Within this context, the ultimate objective of this dissertation lies in the development and implementation of efficient control strategies for autonomous single and multiple underwater robotic systems considering significant issues such as: external disturbances, limited power resources, strict communication constraints along with underwater sensing and localization issues. Specifically, we focused on cooperative and interaction control methodologies for single and multiple Underwater Vehicle Manipulator Systems (UVMSs) considering the aforementioned issues and limitations, a topic of utmost challenging area of marine robotics. More precisely, the contributions of this thesis lie in the scope of three topics: i) Motion Control, ii) Visual servoing and iii) Interaction&amp;Cooperative Transportation. In the first part, we formulated in a generic way the problem of Autonomous Underwater Vehicle (AUV) motion operating in a constrained environment including obstacles. Various constraints such as: obstacles, workspace boundaries, thruster saturation, system‘s sensing range and predefined upper bound of the vehicle velocity are considered during the control design. Moreover, the controller has been designed in a way that the vehicle exploits the ocean currents, which results in reduced energy consumption by the thrusters and consequently increases significantly the autonomy of the system. In the second part of the thesis, we have formulated a number of novel visual servoing control strategies in order to stabilize the robot (or robot’s end-effector) close to the point of interest considering significant issues such as: camera Field of View (FoV), Camera Calibration uncertainties and the resolution of visual tracking algorithm. In the third part of the thesis, regarding the interaction task, we present a robust interaction control scheme for a UVMS in contact with the environment, with great applications in underwater robotics (e.g. sampling of the sea organisms, underwater welding, object handling). The proposed control scheme does not required any a priori knowledge of the UVMS dynamical parameters or the stiffness model. It guarantees a predefined behavior in terms of desired overshoot, transient and steady state response and it is robust with respect to external disturbances and measurement noises. Moreover, we have addressed the problem of cooperative object transportation for a team of UVMSs in a constrained workspace involving static obstacles. First, for case when the robots are equipped with appropriate force/torque sensors at its end effector we have proposed a decentralized impedance control scheme with the coordination relying solely on implicit communication arising from the physical interaction of the robots with the commonly grasped object. Second, for case when the robots are not equipped with force/torque sensor at it end effector, we have proposed a decentralized predictive control approach which takes into account constraints that emanate from control input saturation as well kinematic and representation singularities. Finally, numerical simulations performed in MATLAB and ROS environments, along with extensive real-time experiments conducted with available Control Systems Lab (CSL) robotic equipment, demonstrate and verify the effectiveness of the claimed results.QC 20190514</p

Cooperative and Interaction Control for Underwater Robotic Vehicles

In this dissertation we address the problem of robust control for underwater robotic vehicles under resource constraints and inspired by practical applications in the field of marine robotics. By the term “resource constraints” we refer to systems with constraints on communication, sensing and energy resources. Within this context, the ultimate objective of this dissertation lies in the development and implementation of efficient control strategies for autonomous single and multiple underwater robotic systems considering significant issues such as: external disturbances, limited power resources, strict communication constraints along with underwater sensing and localization issues. Specifically, we focused on cooperative and interaction control methodologies for single and multiple Underwater Vehicle Manipulator Systems (UVMSs) considering the aforementioned issues and limitations, a topic of utmost challenging area of marine robotics. More precisely, the contributions of this thesis lie in the scope of three topics: i) Motion Control, ii) Visual servoing and iii) Interaction&amp;Cooperative Transportation. In the first part, we formulated in a generic way the problem of Autonomous Underwater Vehicle (AUV) motion operating in a constrained environment including obstacles. Various constraints such as: obstacles, workspace boundaries, thruster saturation, system‘s sensing range and predefined upper bound of the vehicle velocity are considered during the control design. Moreover, the controller has been designed in a way that the vehicle exploits the ocean currents, which results in reduced energy consumption by the thrusters and consequently increases significantly the autonomy of the system. In the second part of the thesis, we have formulated a number of novel visual servoing control strategies in order to stabilize the robot (or robot’s end-effector) close to the point of interest considering significant issues such as: camera Field of View (FoV), Camera Calibration uncertainties and the resolution of visual tracking algorithm. In the third part of the thesis, regarding the interaction task, we present a robust interaction control scheme for a UVMS in contact with the environment, with great applications in underwater robotics (e.g. sampling of the sea organisms, underwater welding, object handling). The proposed control scheme does not required any a priori knowledge of the UVMS dynamical parameters or the stiffness model. It guarantees a predefined behavior in terms of desired overshoot, transient and steady state response and it is robust with respect to external disturbances and measurement noises. Moreover, we have addressed the problem of cooperative object transportation for a team of UVMSs in a constrained workspace involving static obstacles. First, for case when the robots are equipped with appropriate force/torque sensors at its end effector we have proposed a decentralized impedance control scheme with the coordination relying solely on implicit communication arising from the physical interaction of the robots with the commonly grasped object. Second, for case when the robots are not equipped with force/torque sensor at it end effector, we have proposed a decentralized predictive control approach which takes into account constraints that emanate from control input saturation as well kinematic and representation singularities. Finally, numerical simulations performed in MATLAB and ROS environments, along with extensive real-time experiments conducted with available Control Systems Lab (CSL) robotic equipment, demonstrate and verify the effectiveness of the claimed results.QC 20190514</p