GHO-WBC: A Gradient-Based Hierarchical Kinematic Optimization Approach to Enhance the Reachability of a Humanoid Robot
Weiliang Zhu, Guoteng Zhang, Liaochao Qiao, Ligang Ge, Yibin Li
Abstract
Humanoid robots are vital tools for substituting humans in various operational scenarios. A sufficiently large stationary reachability is a key factor in ensuring their operational capability. To address this challenge, this paper proposes a whole-body reachability enhancing approach for humanoid robots based on gradient optimization, referred to as Gradient-based Hierarchical Optimization Whole-Body Control (GHO-WBC). The goal of the proposed approach is to extend the end-effector reachability of the humanoid robot while maintaining its stationary state. The proposed approach first derives the gradient of the robot’s whole-body center of mass (CoM) position, ensuring stationary stability across extreme reachable ranges. Next, the gradient of the key joint segment singularity is derived to achieve the stability of the humanoid robot’s end effector at extreme operational distances. Finally, a multi-level optimization approach is employed to compute a feasible solution for the whole-body joint kinematics, and experimental validation is conducted on the humanoid robot. Compared to the conventional whole-body control optimization approach, the present approach improves the reachable range by more than 89%.
BibTeX
@inproceedings{iros2025_ghowbcagradientb,
title = {GHO-WBC: A Gradient-Based Hierarchical Kinematic Optimization Approach to Enhance the Reachability of a Humanoid Robot},
author = {Weiliang Zhu and Guoteng Zhang and Liaochao Qiao and Ligang Ge and Yibin Li},
booktitle = {IROS 2025},
year = {2025}
}