DCARE: Decentralized Collaborative Autonomous Robotic Exploration
Leyi Zhao, Chi Chen, Shangzhe Sun, Liuchun Li, Ang Jin, Zongtian Hu, Yuhang Xu, Bisheng Yang · 2024
Autonomous exploration of complex unknown environment challenges the intelligent perception and navigation abilities of unmanned system. Traditional single-robot method suffers from low efficiency and low risk resistance capacity. This paper introduces a decentralized multi-robot autonomous exploration system DCARE that can collaboratively explore complex environment with LiDAR. On the single-robot layer, we develop a frontier-based exploration strategy with deciding exploration goal based on information gain, then a probabilistic-based controller is utilized to navigate the robot. On the multi-robot layer, robots share and incrementally merge perceived map and states, thus robots cooperate based on the combined information. We have conducted experiment in a maze with random pillars and walls, the proposed method finishes the exploration in 383$s$with 95% spatial coverage rate, achieves 72% improvement in exploration efficiency.