Footstep adaptation strategy for reactive omnidirectional walking in humanoid robots. Issue 1 (12th April 2017)

• Record Type: Journal Article
• Authors: Zhang, Jiwen; Xia, Zeyang; Liu, Li; Chen, Ken
• Is Part Of: Robotica. Volume 36:Issue 1(2018)
• Page Start: 57
• Page End: 77
• Publication Date: 2017-04-12
• Subjects: Humanoid robots, -- Omnidirectional, -- Reactive walking, -- Inverted pendulum model, -- Nonlinear optimization, -- Surrogate model optimization; Robots -- Periodicals; 629.89205
• DOI: 10.1017/S0263574717000157
• Languages: English
• ISSNs: 0263-5747

Abstract

SUMMARY: Stability, high response quality and rapidity are required for reactive omnidirectional walking in humanoids. Early schemes focused on generating gaits for predefined footstep locations and suffered from the risk of falling over because they lacked the ability to suitably adapt foot placement. Later methods combining stride adaptation and center of mass (COM) trajectory modification experienced difficulties related to increasing computing loads and an unwanted bias from the desired commands. In this paper, a hierarchical planning framework is proposed in which the footstep adaption task is separated from that of COM trajectory generation. A novel omnidirectional vehicle model and the inequalities deduced therefrom are adopted to describe the inter-pace connection relationship. A constrained nonlinear optimization problem is formulated and solved based on these inequalities to generate the optimal strides. A black-box optimization problem is then constructed and solved to determine the model constants using a surrogate-model-based approach. A simulation-based verification of the method and its implementation on a physical robot with a strictly limited computing capacity are reported. The proposed method is found to offer improved response quality while maintaining rapidity and stability, to reduce the online computing load required for reactive walking and to eliminate unnecessary bias from walking intentions.