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In this paper, we propose a locomotion planning framework for a humanoid robot with an efficient footstep and whole-body collision avoidance planning, which enables the robot to traverse an unknown narrow space while utilizing its body structure like a human. The key idea of the proposed method is to reduce a large computational cost for the whole-body locomotion planning by executing global footstep planning first, which has a much smaller search space, and then performing a sequential whole-body posture planning while utilizing the resulting footsteps and a centroidal trajectory as a guide. In the global footstep planning phase, we modify bounding box of the robot based on the centroidal sway motion. This idea enables the planner to obtain appropriate footsteps for next whole-body motion planning. Then, we execute sequential whole-body collision avoidance motion planning by prioritized inverse kinematics based on the resulting footsteps and centroidal trajectory, which enables the robot to plan whole-body collision avoidance motion for each step within less than 100ms at worst. The major contribution of our paper is solving the problem of the increasing computational cost for whole-body motion planning and enabling a humanoid robot to execute adaptive locomotion planning on the spot in an unknown narrow space.
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Kumagai et al. (2018) studied this question.
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