A Three-Stage Offline SDRE-Based Control Framework for Human Motion Reproduction on a Suspended Bipedal Robot
Ping-Kong Huang, Chien-Wu Lan, Chin-Tien Wu, Ching-Kai Lin

TL;DR
This paper introduces a three-stage offline control framework utilizing SDRE, optimization, and PID-LQR methods to accurately reproduce human motion on a suspended bipedal robot for exoskeleton testing.
Contribution
It presents a novel three-stage control strategy combining model-based, optimization, and data-driven techniques for precise human motion reproduction on robots.
Findings
Achieved average RMSE below 3 degrees in motion tracking.
Validated the control framework on a suspended bipedal robot platform.
Demonstrated high fidelity in reproducing squatting and walking motions.
Abstract
During the development of wearable exoskeletons, evaluations involving human subjects pose inherent safety risks. Therefore, systematic testing is often conducted using robots that emulate human motion. However, reproducing human movements is challenging due to differences in robot structure and actuator characteristics. This study proposes a three-stage offline control strategy that uses motion-capture data and robot-specific properties to generate control commands for accurate motion replication. First, an optimal torque trajectory is generated via a State-Dependent Riccati Equation (SDRE) controller based on the dynamic model of the bipedal system. Second, joint velocity and acceleration command sequences are synthesized through parameterized optimization under actuator constraints. Finally, a data-driven PID-LQR offline controller refines these commands by minimizing the tracking…
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