Pareto Optimal Reconfiguration Planning and Distributed Parallel Motion Control of Mobile Modular Robots
Chen Zhang, Lelai Zhou, Yibin Li
Abstract
Aiming at improving the efficiency of reconfiguration of mobile modular robots, the optimal reconfiguration planning and parallel control method are proposed in this work. The number of moving modules, the number of undocking actions, and the total moving distance are considered in reconfiguration optimization with the lexicographic framework. The maximum common subgraph matching and searching tree are proposed to search the Pareto optimal solution. A distributed controller based on local consensus is designed for components that are rigidly connected by different numbers of modules and under different shapes. Parallel motion in the shared workspace brings a high efficiency of reconfiguration. The simulations and real-world experiments verify the effectiveness of our method.