mlsanityData to 14 Oct 2026

CT-CPP: Coverage Path Planning for 3D Terrain Reconstruction Using Dynamic Coverage Trees

arXiv 2010.09231 ↗First posted 19 Oct 2020cs.RO cs.AI cs.SYcited by 4

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Abstract (arXiv)

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.

Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 19 Oct 2020.

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Citing papers per year: 2021: 1; 2022: 0; 2023: 0; 2024: 0; 2025: 2; 2026: 1.

4 papers.