A Novel Graph-based Motion Planner of Multi-Mobile Robot Systems with Formation and Obstacle Constraints

TL;DR

This paper introduces a novel graph-based motion planning method for multi-mobile robot systems that ensures formation and obstacle constraints are satisfied while finding optimal paths in complex environments.

Contribution

It presents a new approach that maps workspace to configuration space, constructs a connectivity graph, and plans optimal paths considering formation and obstacle constraints.

Findings

Successfully plans optimal paths in obstacle-rich environments

Handles formation constraints effectively

Considers multiple constraints in path planning

Abstract

Multi-mobile robot systems show great advantages over one single robot in many applications. However, the robots are required to form desired task-specified formations, making feasible motions decrease significantly. Thus, it is challenging to determine whether the robots can pass through an obstructed environment under formation constraints, especially in an obstacle-rich environment. Furthermore, is there an optimal path for the robots? To deal with the two problems, a novel graphbased motion planner is proposed in this paper. A mapping between workspace and configuration space of multi-mobile robot systems is first built, where valid configurations can be acquired to satisfy both formation constraints and collision avoidance. Then, an undirected graph is generated by verifying connectivity between valid configurations. The breadth-first search method is employed to answer the question of whether there is a feasible path on the graph. Finally, an optimal path will be planned on the updated graph, considering the cost of path length and formation preference. Simulation results show that the planner can be applied to get optimal motions of robots under formation constraints in obstacle-rich environments. Additionally, different constraints are considered.