LECES: A Low-Bandwidth and Efficient Collaborative Exploration System With Distributed Multi-UAV

Collaborative exploration is a prevailing trend of autonomous exploration by unmanned aerial vehicles (UAVs). However, most collaborative exploration systems rely on excessively high communication bandwidth for precise map maintenance and efficient task allocation. This letter proposes a low-bandwidth and efficient collaborative exploration system with distributed multi-UAV. First, a lightweight map fusion method is proposed, based on Binary OctoMap with a sliding cube, to incrementally maintain a consistent global map for all UAVs with low bandwidth cost. Then, an efficient exploration strategy is proposed that decouples the multi-UAV task allocation problem into independent single-UAV Asymmetric Traveling Salesman Problems (ATSP) based on the consistent global map. By viewpoints clustering, assignment, and decision, it allows for efficient task allocation without iterative interactions. Experiments are conducted in both simulations and real-world environments. The experiment results demonstrate that our method achieves stable and efficient exploration with low communication bandwidth requirements.