RACER: Rapid Collaborative Exploration with a Decentralized Multi-UAV System

Abstract--Although the use of multiple Unmanned Aerial Vehicles (UAVs) has great potential for fast autonomous exploration, it has received far too little attention. To effectively dispatch the UAVs, a pairwise interaction based on an online hgrid space decomposition is used. It ensures that all UAVs simultaneously explore distinct regions, using only asynchronous and limited communication. Further, we optimize the coverage paths of unknown space and balance the workloads partitioned to each UAV with a Capacitated Vehicle Routing Problem(CVRP) formulation. Given the task allocation, each UAV constantly updates the coverage path and incrementally extracts crucial information to support the exploration planning. A hierarchical planner finds exploration paths, refines local viewpoints and generates minimum-time trajectories in sequence to explore the unknown space agilely and safely. The proposed approach is evaluated extensively, showing high exploration efficiency, scalability and robustness to limited communication. Furthermore, for the first time, we achieve fully decentralized collaborative exploration with multiple UAVs in real world. Two quadrotors simultaneously explore a complex unknown environment. It is demonstrated that UAVs are particularly suited to exploring complex environments efficiently, thanks to their the coordination vulnerable and less effective. To improve the agility and flexibility. Secondly, many multi-robot exploration approaches been paid to multi-UAV systems. However, using a fleet solely consider the allocation of frontiers or viewpoints. of UAVs has incredible potential, since it not only enables Because the actual regions explored by each UAV are not faster accomplishment of exploration, but also is more faulttolerant accounted for, the strategies often result in interference among than a single UAV.