CT-CPP: Coverage Path Planning for 3D Terrain Reconstruction Using Dynamic Coverage Trees
Zongyuan Shen, Junnan Song, Khushboo Mittal, Shalabh Gupta · IEEE Robotics and Automation Letters · 2021
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.