Abstract
The hexapod robot is widely used in rough terrain environments due to its flexible and stable locomotion. However, it is hard for the hexapod robot to avoid the dynamic and static obstacles in real time during the motion planning process. To address this problem, in this article, we propose a novel integrated motion planner. The global planner employs the Bidirectional-RRT <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∗</sup> algorithm to find a feasible solution at first, then the TEB algorithm is used in the local planner to optimize the current solution in real time. We conduct a series of simulation experiments in dynamic rough terrain environments, and the results demonstrate that our proposed method can achieve better performance on the motion planning process for the hexapod robot.
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