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首页> 外文期刊>Mathematical Problems in Engineering >Constrained Quadratic Programming and Neurodynamics-Based Solver for Energy Optimization of Biped Walking Robots
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Constrained Quadratic Programming and Neurodynamics-Based Solver for Energy Optimization of Biped Walking Robots

机译：约束二次规划和基于神经动力学的求解器，用于两足步行机器人的能量优化

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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.
机译：双足机器人的应用总是被其高能耗所困。本文通过优化关节扭矩以降低能耗而不改变两足动物步态做出了贡献。在这项工作中，提出了用于能量优化的约束二次规划（QP）问题。提出了一种基于神经动力学的求解器来解决QP问题。与现有文献不同，所提出的基于神经动力学的能量优化（NEO）策略可最大程度地减少能量消耗并同时确保以下三个重要约束：（i）两足机器人的力力矩平衡方程，（ii）每个机器人施加的摩擦力将脚放在地面上以保持两足动物机器人不打滑和倾翻，以及（iii）电动机的物理极限。仿真表明，所提出的策略对于节能的两足动物步行是有效的。

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  • 来源
    《Mathematical Problems in Engineering》 |2017年第9期|6725427.1-6725427.15|共15页
  • 作者

    Wang Liyang; Chen Ming; Jiang Xiangkui; Wang Wei;

  • 作者单位

    Shunde Polytech, Dept Elect Engn, Foshan 528300, Guangdong, Peoples R China;

    Shunde Polytech, Dept Elect Engn, Foshan 528300, Guangdong, Peoples R China;

    Xian Univ Posts & Telecommun, Sch Automat, Xian 710121, Shaanxi, Peoples R China;

    Wuhan Univ, Coll Power & Mech Engn, Wuhan 430072, Hubei, Peoples R China;

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