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Impact-Aware Online Motion Planning for Fully-Actuated Bipedal Robot Walking

Yuan Gao, Xingye Da, Yan Gu

Year
2019
Citations
2
Access
Open access

Abstract

The ability to track a general walking path with specific timing is crucial to the operational safety and reliability of bipedal robots for avoiding dynamic obstacles, such as pedestrians, in complex environments. This paper introduces an online, full-body motion planner that generates the desired impact-aware motion for fully-actuated bipedal robotic walking. The main novelty of the proposed planner lies in its capability of producing desired motions in real-time that respect the discrete impact dynamics and the desired impact timing. To derive the proposed planner, a full-order hybrid dynamic model of fully-actuated bipedal robotic walking is presented, including both continuous dynamics and discrete lading impacts. Next, the proposed impact-aware online motion planner is introduced. Finally, simulation results of a 3-D bipedal robot are provided to confirm the effectiveness of the proposed online impact-aware planner. The online planner is capable of generating full-body motion of one walking step within 0.6 second, which is shorter than a typical bipedal walking step.

Keywords

PlannerRobotMotion (physics)Computer scienceMotion planningSimulationNoveltyControl theory (sociology)Control engineeringArtificial intelligence

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