Robust Path Planning Against Pose Errors for Mobile Robots in Rough Terrain
We propose a novel path planning method considering pose errors for off-road mobile robots based on 3D terrain map information. Mobile robots navigating on rough terrain cannot follow a planned path perfectly because of uncertainties such as pose errors. In this work, we represent such pose errors as error ellipsoids to use on collision check with obstacles in a map. The error ellipsoids are estimated based on extended Kalman filter (EKF) that integrates motion errors and global positioning systems (GPS) observation errors. Simulation and experiment results show that the proposed method enables mobile robots to generate a robust path against pose errors in a large-scale rough terrain map.
KeywordsPath planning Rough terrain Random sampling Extended Kalman Filter Error ellipsoid
This work was in part funded by ImPACT Program of Council for Science, Technology and Innovation (Cabinet Office, Government of Japan).
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