A Three-Stage Offline SDRE-Based Control Framework for Human Motion Reproduction on a Suspended Bipedal Robot

arXiv:2506.04680v2 Announce Type: replace 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 error between the desired and executed motions. Experimental validation is performed on a suspended bipedal robot platform designed for the evaluation of gravity-counteracting exoskeletons. Motion-capture data collected from squatting and walking tasks are used for system assessment. The experimental results demonstrate high tracking fidelity, with an average root mean square error (RMSE) below 3 degrees. These results verify the effectiveness of the proposed three-stage control strategy for robot-based systematic testing of exoskeletons.