Mixed Control for Whole-Body Compliance of a Humanoid Robot
Xiaozhu Ju, Jiajun Wang, Gang Han, Mingguo Zhao

TL;DR
This paper introduces a mixed control approach combining MPC and PD control to improve whole-body compliance in humanoid robots, addressing oscillations near constraints and enabling high-frequency servo control.
Contribution
It proposes a novel mixed control strategy that integrates MPC and PD control with an efficient null space projection for improved compliance and real-time performance.
Findings
MPC predicts constraint boundaries for smooth control
The approach achieves 500 Hz control rate in experiments
Validation on Walker X demonstrates improved compliance
Abstract
The hierarchical quadratic programming (HQP) is commonly applied to consider strict hierarchies of multi-tasks and robot's physical inequality constraints during whole-body compliance. However, for the one-step HQP, the solution can oscillate when it is close to the boundary of constraints. It is because the abrupt hit of the bounds gives rise to unrealisable jerks and even infeasible solutions. This paper proposes the mixed control, which blends the single-axis model predictive control (MPC) and proportional derivate (PD) control for the whole-body compliance to overcome these deficiencies. The MPC predicts the distances between the bounds and the control target of the critical tasks, and it provides smooth and feasible solutions by prediction and optimisation in advance. However, applying MPC will inevitably increase the computation time. Therefore, to achieve a 500 Hz servo rate, the…
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Taxonomy
TopicsGenetic Neurodegenerative Diseases · Prosthetics and Rehabilitation Robotics · Muscle Physiology and Disorders
