This letter addresses the 3D coverage path planning (CPP) problem for terrain reconstruction of unknown obstacle rich environments. Due to sensing limitations, the proposed method, called CT-CPP, performs layered scanning of the 3D region to collect terrain data, where the traveling sequence is optimized using the concept of a coverage tree (CT) with a TSP-inspired tree traversal strategy. The CT-CPP method is validated on a high-fidelity underwater simulator and the results are compared to an existing terrain following CPP method. The results show that CT-CPP yields significant reduction in trajectory length, energy consumption, and reconstruction error.

翻译：由于遥感方面的限制,拟议的方法(称为CT-CPP)对3D区域进行分层扫描,以收集地形数据,在3D区域使用由TSP启发的树木穿行战略的覆盖树(CT)概念优化了旅行顺序,在高纤维水下模拟器上验证了CT-CPP方法,并将结果与采用CPP方法的现有地形进行比较,结果显示CT-CPP在轨迹长度、能源消耗和重建错误方面大为减少。