Collision and Deadlock Avoidance in Multirobot Systems: A Distributed Approach

Abstract

Collision avoidance is a critical problem in motion 1 planning and control of multirobot systems. Moreover, it may 2 induce deadlocks during the procedure to avoid collisions. In 3 this paper, we study the motion control of multirobot systems 4 where each robot has its own predetermined and closed path 5 to execute persistent motion. We propose a real-time and dis-6 tributed algorithm for both collision and deadlock avoidance by 7 repeatedly stopping and resuming robots. The motion of each 8 robot is first modeled as a labeled transition system, and then 9 controlled by a distributed algorithm to avoid collisions and dead-10 locks. Each robot can execute the algorithm autonomously and 11 real-timely by checking whether its succeeding state is occupied 12 and whether the one-step move can cause deadlocks. Performance 13 analysis of the proposed algorithm is also conducted. The con-14 clusion is that the algorithm is not only practically operative but 15 also maximally permissive. A set of simulations for a system with 16 four robots are carried out in MATLAB. The results also validate 17 the effectiveness of our algorithm. 18 Index Terms-Collision and deadlock avoidance, discrete event 19 systems, distributed algorithm, maximally permissive, motion 20 control, multirobot systems. 21 I. INTRODUCTION 22 C OMPARED with their single-robot counterparts, 23 multirobot systems become increasingly prevailing 24 thanks to their benefits like wide coverage, diverse func-25 tionality, and strong flexibility [18]. Besides, with the 26 collective behavior of multiple robots, a multirobot system 27 has the enthralling capability to accomplish sophisticated 28 tasks [20]. Multirobot systems have been applied in many 29

Honeycomb Map: A Bioinspired Topological Map for Indoor Search and Rescue Unmanned Aerial Vehicles

“…Several approaches have been presented, where means of prevention are proposed by optimized programming [23][24][25], potential fields [26], sampling-based methods [27], and others. In general, two concepts are applied [28]: one where robots are free and can change their paths, and another where robots have a fixed path with no possibility of changes. Thus, in the first concept, the focus is on changing paths, while in the second, the focus is on controlling movement and time.…”

“…In [28] a method for treating deadlock for multiple robots where the path is fixed is discussed. To improve performance, some stopping policies are proposed.…”

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“…Most existing research focused on motion planning of autonomous systems sharing the environment with the guarantees of safety (i.e., the collision shall never happen) and liveness (i.e., travel to the destination eventually) [9]- [13]. For example, distributed approaches are proposed in [9], [10] to avoid collisions and deadlocks in multi-robot systems. In more complex scenarios, time, energy, and visibility constraints are taken into consideration [2], [14].…”

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