Formation Control and Distributed Goal Assignment for Multi-Agent Non-Holonomic Systems

Abstract

This paper presents control algorithms for multiple non-holonomic mobile robots moving in formation. Trajectory tracking based on linear feedback control is combined with inter-agent collision avoidance. Artificial potential functions (APF) are used to generate a repulsive component of the control. Stability analysis is based on a Lyapunov-like function. Then the presented method is extended to include a goal exchange algorithm that makes the convergence of the formation much more rapid and, in addition, reduces the number of collision avoidance interactions. The extended method is theoretically justified using a Lyapunov-like function. The controller is discontinuous but the set of discontinuity points is of zero measure. The novelty of the proposed method lies in integration of the closed-loop control for non-holonomic mobile robots with the distributed goal assignment, which is usually regarded in the literature as part of trajectory planning problem. A Lyapunov-like function joins both trajectory tracking and goal assignment analyses. It is shown that distributed goal exchange supports stability of the closed-loop control system. Moreover, robots are equipped with a reactive collision avoidance mechanism, which often does not exist in the known algorithms. The effectiveness of the presented method is illustrated by numerical simulations carried out on the large formation of robots.

A Multi-Switching Tracking Control Scheme for Autonomous Mobile Robot in Unknown Obstacle Environments

“…where k 1 , k 2 , and k 3 are positive constants. the control inputs described in Equations (2) and 3are used, the tracking errors e 1 , e 2 , and e 3 will converge to zero.…”

“…In recent years, the wheeled mobile robot (WMR) has received much attention due to its many practical applications, which is widely used in various aspects, such as search and rescue [1], multi-robotic formation [2,3], industrial applications [4,5], military operations [6,7], and so on. These applications require the mobile robot to move autonomously and carry out a variety of automated tasks which include trajectory tracking, obstacle avoidance, formation control, etc.…”

Special Feature on Advanced Mobile Robotics

“…Multi-agent robots have been applied to formation control by Kowalczyk [5] and its control is integrated with distributed goal assignment. Biologically-inspired learning and adaptation can even be applied to control of networked mobile robots.…”

Integral-Type Edge-Event- and Edge-Self-Triggered Synchronization to Multi-Agent Systems with Lur’e Nonlinear Dynamics

“…In recent years, distributed control of multi-agent systems has emerged as an essential topic in the field of control theory [1][2][3][4][5][6][7][8][9][10][11][12], and it has been applied in more and more fields such as the coordinated attitude of multiple spacecraft, formation cooperative control, multi-drone coordination, and multiple robotic arms coordination. The main concern on distributed control is how to coordinate all individuals to achieve synchronization and consensus control under information interaction [1,2,5,6].…”