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3D Scan matching for mobile robot localization over rough terrain

Hiroyuki Nakagomi, Yoshihiro Fuse, Hidehiko Hosaka, Hironaga Miyamoto, Takashi Nakamura, Akira Yoneyama, Masashi Yokotsuka, Akiya Kamimura, Hiromi Watanabe, Tsutomu Tanzawa, Shinji Kotani

发表年份
2019
引用次数
5
访问权限
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摘要

Abstract In order to enable an autonomous mobile robot to travel over rough terrain, it necessitates the capability to detect self‐position accurately even when the odometry errors are increased in traveling. The conventional method can keep high speed and precise localization using iterative closest point algorithms or feature matching techniques. However, effects of steep changes of a mobile robot position are not considered when it travels over rough terrain. In this article, we propose the method for efficient real‐time 6D pose tracking using a rotating 2D laser scanner in traveling over rough terrain. For adaptation to steep changes of the position, weighted point clouds are generated based on the angular and the linear velocity measured by sensors mounted on the robot. And the position and posture of the robot are sequentially optimized by the scan matching in increments of 10 scans. In indoor experiments, we evaluated accuracy of our method when the robot passes on rugged floor. As a result, our method was performed with less than 0.078 m RMS positional error in real time.

关键词

OdometryComputer visionTerrainArtificial intelligenceMobile robotComputer scienceRobotIterative closest pointPosition (finance)Matching (statistics)

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