Formation navigation with relative distance maintenance in obstacle environments
Danxu Li, Zhi Li, Shaohui Li, Huajie Wang, Yu Liu · 2024
In recent years, with the increasing adoption of robots and the limitations in the safety and efficiency of individual robots, the study of multi-robot formation navigation has gained widespread attention. However, achieving deadlock-free formation navigation with robots maintaining relative distances in obstacle environments remains a significant challenge, particularly in coordinating the tasks of obstacle avoidance and formation maintenance. Addressing this challenge, we propose a framework for robot formation navigation in obstacle environments. Initially, we employ formation-level global path planning to search for global paths that consider both translational and rotational movements of the formation, offering better coordination between obstacle avoidance and formation maintenance conflicts. Subsequently, through a distributed optimization algorithm for robot trajectories under formation constraints, we locally optimize the global paths, enabling robots to dynamically balance obstacle avoidance and distance maintenance tasks during navigation. Finally, we validate the effectiveness of this approach through simulation experiments, demonstrating its practical applicability in complex environments.