Experimental Investigations into Using Motion Capture State Feedback for Real-Time Control of a Humanoid Robot

Mihaela Popescu; Dennis Mronga; Ivan Bergonzani; Shivesh Kumar; Frank Kirchner

In: Sensors - Open Access Journal (Sensors), Vol. 22, No. 24, Pages 1-12, Multidisciplinary Digital Publishing Institute (MDPI), 12/2022.


Regardless of recent advances, humanoid robots still face significant difficulties in performing locomotion tasks. Among the key challenges that must be addressed to achieve robust bipedal locomotion are dynamically consistent motion planning, feedback control, and state estimation of such complex systems. In this paper, we investigate the use of an external motion capture system to provide state feedback to an online whole-body controller. We present experimental results with the humanoid robot RH5 performing two different whole-body motions: squatting with both feet in contact with the ground and balancing on one leg. We compare the execution of these motions using state feedback from (i) an external motion tracking system and (ii) an internal state estimator based on inertial measurement unit (IMU), forward kinematics, and contact sensing. It is shown that state-of-the-art motion capture systems can be successfully used in the high-frequency feedback control loop of humanoid robots, providing an alternative in cases where state estimation is not reliable.


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Deutsches Forschungszentrum für Künstliche Intelligenz
German Research Center for Artificial Intelligence