不整地における車両型ロボットのための効率的な軌道計画
An Efficient Trajectory Planner for Car-like Robots on Uneven Terrain
不整地の影響をSE(2)からSE(3)への姿勢マッピングで表現し、車両型ロボットの動力学モデルに沿った追従性の高い軌道を生成する最適化フレームワークを提案した。
著者: Long Xu, Kaixin Chai, Zhichao Han, Hong Liu, Chao Xu, Yanjun Cao, Fei Gao
分類: cs.RO
原文アブストラクト
Autonomous navigation of ground robots on uneven terrain is being considered in more and more tasks. However, uneven terrain will bring two problems to motion planning: how to assess the traversability of the terrain and how to cope with the dynamics model of the robot associated with the terrain. The trajectories generated by existing methods are often too conservative or cannot be tracked well by the controller since the second problem is not well solved. In this paper, we propose terrain pose mapping to describe the impact of terrain on the robot. With this mapping, we can obtain the SE(3) state of the robot on uneven terrain for a given state in SE(2). Then, based on it, we present a trajectory optimization framework for car-like robots on uneven terrain that can consider both of the above problems. The trajectories generated by our method conform to the dynamics model of the system without being overly conservative and yet able to be tracked well by the controller. We perform simulations and real-world experiments to validate the efficiency and trajectory quality of our algorithm.
