Task-Space Riccati Feedback based Whole Body Control for Underactuated Legged Locomotion
<|reference_start|>Task-Space Riccati Feedback based Whole Body Control for Underactuated Legged Locomotion: This manuscript primarily aims to enhance the performance of whole-body controllers(WBC) for underactuated legged locomotion. We introduce a systematic parameter design mechanism for the floating-base feedback control within the WBC. The proposed approach involves utilizing the linearized model of unactuated dynamics to formulate a Linear Quadratic Regulator(LQR) and solving a Riccati gain while accounting for potential physical constraints through a second-order approximation of the log-barrier function. And then the user-tuned feedback gain for the floating base task is replaced by a new one constructed from the solved Riccati gain. Extensive simulations conducted in MuJoCo with a point bipedal robot, as well as real-world experiments performed on a quadruped robot, demonstrate the effectiveness of the proposed method. In the different bipedal locomotion tasks, compared with the user-tuned method, the proposed approach is at least 12% better and up to 50% better at linear velocity tracking, and at least 7% better and up to 47% better at angular velocity tracking. In the quadruped experiment, linear velocity tracking is improved by at least 3% and angular velocity tracking is improved by at least 23% using the proposed method.<|reference_end|>
@article{yang2024task-space,
    title={Task-Space Riccati Feedback based Whole Body Control for Underactuated
  Legged Locomotion},
    author={Shunpeng Yang, Zejun Hong, Sen Li, Patrick Wensing, Wei Zhang and Hua
  Chen},
    journal={arXiv preprint arXiv:2404.00591},
    year={2024},
    archivePrefix={arXiv},
    eprint={2404.00591},
    primaryClass={cs.RO}
}