異種航空システムのための低コスト協調探索・検査戦略
A Cost-Effective Cooperative Exploration and Inspection Strategy for Heterogeneous Aerial System
異種ドローン群が環境の事前知識なしに任意形状物体の3D表面を協調探索・検査する低コスト戦略を提案し、ベースラインを公開した。
著者: Xinhang Xu, Muqing Cao, Shenghai Yuan, Thien Hoang Nguyen, Thien-Minh Nguyen, Lihua Xie
分類: cs.RO
原文アブストラクト
In this paper, we propose a cost-effective strategy for heterogeneous UAV swarm systems for cooperative aerial inspection. Unlike previous swarm inspection works, the proposed method does not rely on precise prior knowledge of the environment and can complete full 3D surface coverage of objects in any shape. In this work, agents are partitioned into teams, with each drone assign a different task, including mapping, exploration, and inspection. Task allocation is facilitated by assigning optimal inspection volumes to each team, following best-first rules. A voxel map-based representation of the environment is used for pathfinding, and a rule-based path-planning method is the core of this approach. We achieved the best performance in all challenging experiments with the proposed approach, surpassing all benchmark methods for similar tasks across multiple evaluation trials. The proposed method is open source at https://github.com/ntu-aris/caric_baseline and used as the baseline of the Cooperative Aerial Robots Inspection Challenge at the 62nd IEEE Conference on Decision and Control 2023.
