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http://dx.doi.org/10.4218/etrij.2021-0087

Collision-free local planner for unknown subterranean navigation  

Jung, Sunggoo (Autonomous Flight Research Section, Electronics and Telecommunications Research Institute)
Lee, Hanseob (Unmanned Systems Research Group, KAIST)
Shim, David Hyunchul (Unmanned Systems Research Group, KAIST)
Agha-mohammadi, Ali-akbar (JPL Robotics, NASA-JPL, California Institute of Technology)
Publication Information
ETRI Journal / v.43, no.4, 2021 , pp. 580-593 More about this Journal
Abstract
When operating in confined spaces or near obstacles, collision-free path planning is an essential requirement for autonomous exploration in unknown environments. This study presents an autonomous exploration technique using a carefully designed collision-free local planner. Using LiDAR range measurements, a local end-point selection method is designed, and the path is generated from the current position to the selected end-point. The generated path showed the consistent collision-free path in real-time by adopting the Euclidean signed distance field-based grid-search method. The results consistently demonstrated the safety and reliability of the proposed path-planning method. Real-world experiments are conducted in three different mines, demonstrating successful autonomous exploration flights in environment with various structural conditions. The results showed the high capability of the proposed flight autonomy framework for lightweight aerial robot systems. In addition, our drone performed an autonomous mission in the tunnel circuit competition (Phase 1) of the DARPA Subterranean Challenge.
Keywords
Aerial autonomy; drone; GPS-denied navigation; path-planning; subterranean;
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