A Gait Optimization Smoothing Penalty Function Method for Bipedal Robot via DMOC*. Issue 28 (2015)

• Record Type: Journal Article
• Authors: Sun, Zhongbo; Li, Hongyang; Wang, Jing; Tian, Yantao
• Is Part Of: IFAC-PapersOnLine. Volume 48:Issue 28(2015)
• Page Start: 1148
• Page End: 1153
• Publication Date: 2015
• Subjects: Bipedal robot -- Smoothing penalty function method -- Discrete mechanics and optimal control -- Unconstrained optimization problem -- Modified conjugate gradient method; Automatic control -- Periodicals; 629.805
• DOI: 10.1016/j.ifacol.2015.12.286
• Languages: English
• ISSNs: 2405-8963

Abstract

Abstract: For periodic gait optimization problem of bipedal walking robot, based on discrete mechanics and optimal control (DMOC), a class of smoothing penalty function method is proposed. The optimal control strategy and trajectory are solved by a new smoothing exact penalty function algorithm. The algorithm can quickly converge to a stable gait cycle independent the selection of the initial gait, otherwise, the algorithm only needs one step correction and then generate a stable gait cycle. Numerical simulation results show that the algorithm is feasible and effective. The algorithm makes the bipedal robot walk efficiently and stably on the even terrain.