Rough Terrain Reconstruction for Rover Motion Planning
Computer and Robot Vision（2010）
摘要
A two-step approach is presented to generate a 3D navigable terrain model for robots operating in natural and uneven environment. First an unstructured surface is built from a 360 degrees field of view LIDAR scan. Second the reconstructed surface is analyzed and the navigable space is extracted to keep only the safe area as a compressed irregular triangular mesh. The resulting mesh is a compact terrain representation and allows point-robot assumption for further motion planning tasks. The proposed algorithm has been validated using a large database containing 688 LIDAR scans collected on an outdoor rough terrain. The mesh simplification error was evaluated using the approximation of Hausdorff distance. In average, for a compression level of 93.5%, the error was of the order of 0.5 cm. This terrain modeler was deployed on a rover controlled from the International Space Station (ISS) during the Avatar Explore Space Mission carried out by the Canadian Space Agency in 2009.
更多查看译文
关键词
terrain modeler,navigable terrain model,mesh simplification error,international space station,rough terrain reconstruction,rover motion planning,resulting mesh,canadian space agency,outdoor rough terrain,compact terrain representation,irregular triangular mesh,avatar explore space mission,space missions,lidar,image reconstruction,triangular mesh,laser radar,mesh generation,approximation theory,path planning,space exploration,motion planning,field of view,mobile robots,surface reconstruction,hausdorff distance,surface topography
AI 理解论文
溯源树
样例
生成溯源树，研究论文发展脉络
Chat Paper
正在生成论文摘要