Synchronized Human-Humanoid Motion Imitation
Antonin Dallard, Mehdi Benallegue, Fumio Kanehiro, Abderrahmane Kheddar
Abstract
We present a tele-operation control framework that (i) enhances the upper motion synchrony between a user and a robot using the minimum-jerk model coupled with a recursive least-square filter, and (ii) synchronizes the walking pace by predicting user's stepping frequency using motion capture data and a deep learning model. By integrating (i) and (ii) in a task-space whole-body controller, we achieve full-body synchronization. We assess our humanoid-to-human whole-body synchronized motion model on the HRP-4 humanoid robot in forward, lateral and backward walks with concurrent upper limbs motions experiments.
Topics & Concepts
Humanoid robotJerkSynchronization (alternating current)Computer scienceMotion (physics)ImitationMotion captureControl theory (sociology)Task (project management)RobotFilter (signal processing)Artificial intelligenceComputer visionMotion controlSimulationControl (management)AccelerationEngineeringPhysicsChannel (broadcasting)Classical mechanicsPsychologySocial psychologySystems engineeringComputer networkRobotic Locomotion and ControlMuscle activation and electromyography studiesBalance, Gait, and Falls Prevention