Kostas J. Kyriakopoulos

On the Rendezvous Problem for Multiple Nonholonomic Agents

In this note, a decentralized feedback control strategy that drives a system of multiple nonholonomic unicycles to a rendezvous point in terms of both position and orientation is introduced. The proposed nonholonomic control law is discontinuous and time-invariant and using tools from nonsmooth Lyapunov theory and graph theory the stability of the overall system is examined. Similarly to the linear case, the convergence of the multi-agent system relies on the connectivity of the communication graph that represents the inter-agent communication topology. The control law is first defined in order to guarantee connectivity maintenance for an initially connected communication graph. Moreover, the cases of static and dynamic communication topologies are treated as corollaries of the proposed framework

Nonholonomic navigation and control of cooperating mobile manipulators

This paper presents the first motion planning methodology applicable to articulated, nonpoint nonholonomic robots with guaranteed collision avoidance and convergence properties. It is based on a new class of nonsmooth Lyapunov functions and a novel extension of the navigation function method to account for nonpoint articulated robots. The dipolar inverse Lyapunov functions introduced are appropriate for nonholonomic control and offer superior performance characteristics compared to existing tools. The new potential field technique uses diffeomorphic transformations and exploits the resulting point-world topology. The combined approach is applied to the problem of handling deformable material by multiple nonholonomic mobile manipulators in an obstacle environment to yield a centralized coordinating control law. Simulation results verify asymptotic convergence of the robots, obstacle avoidance, boundedness of object deformations, and singularity avoidance for the manipulators.

Leader–follower cooperative attitude control of multiple rigid bodies

In this paper we extend our previous results on coordinated control of rotating rigid bodies to the case of teams with heterogenous agents. We assume that only a certain subgroup of the agents (the leaders) are vested with the main control objective, that is, maintain constant relative orientation amongst themselves. The rest of the team must meet relaxed control specifications, namely maintain their respective orientations within certain limits dictated by the orientation of the leaders. The proposed control laws respect the limited information each rigid body has with respect to the rest of its peers (leaders or followers) as well as with the rest of the team. Each rigid body is equipped with a control law that utilizes the Laplacian matrix of the associated communication graph, which encodes the communication links between the team members. Similarly to the linear case, the convergence of the multi-agent system relies on the connectivity of the communication graph.

Connectedness Preserving Distributed Swarm Aggregation for Multiple Kinematic Robots

A distributed swarm aggregation algorithm is developed for a team of multiple kinematic agents. Specifically, each agent is assigned a control law, which is the sum of two elements: a repulsive potential field, which is responsible for the collision avoidance objective, and an attractive potential field, which forces the agents to converge to a configuration where they are close to each other. Furthermore, the attractive potential field forces the agents that are initially located within the sensing radius of an agent to remain within this area for all time. In this way, the connectivity properties of the initially formed communication graph are rendered invariant for the trajectories of the closed-loop system. It is shown that under the proposed control law, agents converge to a configuration where each agent is located at a bounded distance from each of its neighbors. The results are also extended to the case of nonholonomic kinematic unicycle-type agents and to the case of dynamic edge addition. In the latter case, we derive a smaller bound in the swarm size than in the static case.

Event-triggered control for discrete-time systems

In this paper, event-triggered strategies for control of discrete-time systems are proposed and analyzed. Similarly to the continuous-time case, the plant is assumed input-to-state stable with respect to measurement errors and the control law is updated once a triggering condition involving the norm of a measurement error is violated. The results are also extended to a self-triggered formulation, where the next control updates are decided at the previous ones, thus relaxing the need for continuous monitoring of the measurement error. The overall framework is then used in a novel Model Predictive Control approach. The results are illustrated through simulated examples.

Minimum jerk path generation

A simple method of trajectory generation of robot manipulators is presented. It is based on an optimal control problem formulation. The jerk, the third derivative of position, of the desired trajectory, adversely affect the efficiency of the control algorithms and therefore should be minimized. assuming joint position, velocity and acceleration to be constrained, a cost criterion containing jerk is considered. Initially, the simple environment without obstacles and constrained by the physical limitations of the joint angles only is examined. For practical reasons, the free execution time has been used to handle the velocity and acceleration constraints instead of the complete bounded state variable formulation. The problem of minimizing the jerk along an arbitrary Cartesian trajectory is formulated and given analytical solution, making this method useful for real-world environments containing obstacles.<<ETX>>

Nonholonomic motion planning for mobile manipulators

A nonholonomic motion planner for mobile manipulators moving in cluttered environments is presented. The approach is based on a discontinuous feedback law under the influence of a special potential field. Convergence is shown via Lyapunovs direct method. Utilizing redundancy, the methodology allows the system to perform secondary, configuration dependent, objectives such as singularity avoidance. It introduces an efficient feedback scheme for real time navigation of nonholonomic systems.

An EMG-Based Robot Control Scheme Robust to Time-Varying EMG Signal Features

Human-robot control interfaces have received increased attention during the past decades. With the introduction of robots in everyday life, especially in providing services to people with special needs (i.e., elderly, people with impairments, or people with disabilities), there is a strong necessity for simple and natural control interfaces. In this paper, electromyographic (EMG) signals from muscles of the human upper limb are used as the control interface between the user and a robot arm. EMG signals are recorded using surface EMG electrodes placed on the users skin, making the users upper limb free of bulky interface sensors or machinery usually found in conventional human-controlled systems. The proposed interface allows the user to control in real time an anthropomorphic robot arm in 3-D space, using upper limb motion estimates based only on EMG recordings. Moreover, the proposed interface is robust to EMG changes with respect to time, mainly caused by muscle fatigue or adjustments of contraction level. The efficiency of the method is assessed through real-time experiments, including random arm motions in the 3-D space with variable hand speed profiles.

A Switching Regime Model for the EMG-Based Control of a Robot Arm

Human-robot control interfaces have received increased attention during the last decades. These interfaces increasingly use signals coming directly from humans since there is a strong necessity for simple and natural control interfaces. In this paper, electromyographic (EMG) signals from the muscles of the human upper limb are used as the control interface between the user and a robot arm. A switching regime model is used to decode the EMG activity of 11 muscles to a continuous representation of arm motion in the 3-D space. The switching regime model is used to overcome the main difficulties of the EMG-based control systems, i.e., the nonlinearity of the relationship between the EMG recordings and the arm motion, as well as the nonstationarity of EMG signals with respect to time. The proposed interface allows the user to control in real time an anthropomorphic robot arm in the 3-D space. The efficiency of the method is assessed through real-time experiments of four persons performing random arm motions.

Closed loop navigation for multiple holonomic vehicles

We extend the navigation function methodology, established for single robot navigation, to the case of multiple robots. Appropriate expressions for the robot potential functions guarantee global convergence. The derived closed form navigation function provides a robust navigation scheme, suitable for real time implementation. The collision avoidance and global convergence properties are verified through simulations.