Decentralized, Unlabeled Multi-Agent Navigation in Obstacle-Rich Environments using Graph Neural Networks
Xuebo Ji,He Li,Zherong Pan,Xifeng Gao,Changhe Tu,Xuebo Ji,He Li,Zherong Pan,Xifeng Gao,Changhe Tu
We propose a decentralized, learning-based solution to the challenging problem of unlabeled multi-agent navigation among obstacles, where robots need to simultaneously tackle the problems of goal assignment, local collision avoidance, and navigation. Our method has each robot infer their desired action by communicating with each other as well as a set of position-fixed routers. The inference is ca...
