A Fault-Tolerant Approach for Modular Robots through Self-Reconfiguration

Abstract

Modular robots have unique advantages in handling faults and improving their robustness due to their self-reconfiguration capacity and homogeneous interchangeability. When locked joint failure occurs in modular robots, the distribution of the failed modules will affect the manipulation capacity of the robot. In this article, a novel self-reconfiguration method that utilizes only the remaining resources available to mitigate the damage caused by module joint failures is proposed. The key node configuration is searched by the particle swarm optimization (PSO) algorithm, and then the collision-free reconfiguration path is planned by the rapidly exploring random trees (RRT) algorithm. The proposed method not only handles single-module lockup failure but can also be expanded to multi-module lockup failures, fully improving the fault tolerance of the modular robot. The method is deployed on the hardware, and the feasibility of the algorithm is verified by self-reconfiguration experiments containing faulty modules.