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Walking Human Trajectory Models and Their Application to Humanoid Robot Locomotion

Isabelle Maroger, Olivier Stasse, Bruno Watier

Year
2020
Citations
18

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.

Keywords

Humanoid robotTrajectoryComputer scienceRobotArtificial intelligenceFocus (optics)SimulationRobot kinematicsPath (computing)Robot control

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