Constrained Quadratic Programming and Neurodynamics-Based Solver for Energy Optimization of Biped Walking Robots

Mathematical Problems in Engineering: Theory, Methods and Applications

Wei Wang¹  Ming Chen²  Liyang Wang²  Xiangkui Jiang³ 

[1] College of Power and Mechanical Engineering, Wuhan University, Wuhan 430072, China, whu.edu.cn;Department of Electronic Engineering, Shunde Polytechnic, Foshan, Guangdong 528300, China, sdpt.com.cn;School of Automation, Xi’an University of Posts and Telecommunications, Xi’an 710121, China, xiyou.edu.cn

DOI  :  10.1155/2017/6725427

学科分类：工程和技术（综合）

来源: Hindawi Publishing Corporation

【 摘 要 】

The application of biped robots is always trapped by their high energy consumption. This paper makes a contribution by optimizing the joint torques to decrease the energy consumption without changing the biped gaits. In this work, a constrained quadratic programming (QP) problem for energy optimization is formulated. A neurodynamics-based solver is presented to solve the QP problem. Differing from the existing literatures, the proposed neurodynamics-based energy optimization (NEO) strategy minimizes the energy consumption and guarantees the following three important constraints simultaneously: (i) the force-moment equilibrium equation of biped robots, (ii) frictions applied by each leg on the ground to hold the biped robot without slippage and tipping over, and (iii) physical limits of the motors. Simulations demonstrate that the proposed strategy is effective for energy-efficient biped walking.

【 授权许可】

CC BY