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

Abstract

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.

Advanced Sensors Technologies Applied in Mobile Robot

“…Ego-motion is computed by iteratively imposing a coplanarity constraint between pairs of detected planner objects in the first step and their associated keypoints in the second step. In [ 2 ], humanoid robot control is reported using state-of-the-art motion capture systems in the high-frequency feedback control loop of humanoid robots. This can be an alternative in cases where state estimation is not reliable.…”

Improving Accuracy of Real-Time Positioning and Path Tracking by Using an Error Compensation Algorithm against Walking Modes

“…Nevertheless, as a replay-based positioning method, it does not allow for good real-time human location. Another solution is to use the method of whole-body wearable motion capture [ 27 ], which detects the location of the person wearing the device. This method can realize real-time positioning, but it can only rely on inertial data for landing detection on the foot.…”