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Optimization Framework of Humanoid Walking Pattern for Human Motion Retargeting

Shimpei Masuda, Ko Ayusawa, Eiichi Yoshida

Year
2018
Citations
2

Abstract

In this paper, we propose a novel method for retargeting human movements including the steps taken by a humanoid robot. For applications, such as wearable device evaluation by a humanoid, it is necessary to reproduce the original human motions as closely as possible and to generate motions that can be realized on a real robot without the robot losing its balance. The proposed method features the optimization framework that integrates the walking pattern generation based on the linear inverted pendulum model whose parameters are optimized to ensure both human likeness and feasibility of the generated motions. The effectiveness of the retargeting method is validated by experiments that reproducing the measured human working motion on the humanoid HRP-4.

Keywords

RetargetingHumanoid robotComputer scienceComputer visionArtificial intelligenceWearable computerRobotMotion (physics)Inverted pendulumHuman motion

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