Rough Terrain Reconstruction for Rover Motion Planning

D. Gingras, T. Lamarche, Jean-Luc Bedwani, E. Dupuis
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引用次数: 38

Abstract

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.
用于漫游车运动规划的粗糙地形重建
提出了一种两步法生成机器人在自然和不均匀环境下的三维可导航地形模型。首先,通过360度激光雷达扫描建立一个非结构化表面。其次,对重建曲面进行分析,提取可航空间,只保留安全区域作为压缩的不规则三角形网格。所得的网格是一个紧凑的地形表示,并允许点机器人假设进一步的运动规划任务。该算法已通过一个大型数据库进行验证,该数据库包含688个在室外粗糙地形上收集的激光雷达扫描。利用Hausdorff距离的近似来评估网格化简误差。平均而言,当压缩水平为93.5%时,误差约为0.5 cm。在加拿大航天局2009年进行的阿凡达探索太空任务期间,该地形建模器部署在国际空间站(ISS)控制的漫游者上。
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