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Walking Human Trajectory Models and Their Application to Humanoid Robot Locomotion

Isabelle Maroger 1 Olivier Stasse 1 Bruno Watier 1
1 LAAS-GEPETTO - Équipe Mouvement des Systèmes Anthropomorphes
LAAS - Laboratoire d'analyse et d'architecture des systèmes
Abstract : In order to fluidly perform complex tasks in collaboration with a human being, such as table handling, a humanoid robot has to recognize and adapt to human movements. To achieve such goals, a realistic model of the human locomotion that is computable on a robot is needed. In this paper, we focus on making a humanoid robot follow a human-like locomotion path. We mainly present two models of human walking which lead to compute an average trajectory of the body center of mass from which a twist in the 2D plane can be deduced. Then the velocities generated by both models are used by a walking pattern generator to drive a real TALOS robot [1]. To determine which of these models is the most realistic for a humanoid robot, we measure human walking paths with motion capture and compare them to the computed trajectories.
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Contributor : Isabelle Maroger <>
Submitted on : Friday, August 28, 2020 - 4:00:07 PM
Last modification on : Wednesday, June 9, 2021 - 10:00:21 AM
Long-term archiving on: : Sunday, November 29, 2020 - 12:06:23 PM


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Isabelle Maroger, Olivier Stasse, Bruno Watier. Walking Human Trajectory Models and Their Application to Humanoid Robot Locomotion. 2020 IEEE/RSJ International Conference on Inteligent Robots and Systems (IROS), Oct 2020, Las Vegas, United States. ⟨10.1109/IROS45743.2020.9341118⟩. ⟨hal-02922573⟩



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