Optimal robot path following for minimal time versus energy loss trade-off using sequential convex programming

Frederik Debrouwere, W. V. Loock, G. Pipeleers, D. Q. Tran, M. Diehl, J. Schutter, J. Swevers
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引用次数: 2

Abstract

This paper focusses on the time-energy optimal path following for robots. This considers the problem of moving along a predetermined geometric path with a minimal trade-off between the motion time and the two major thermal energy losses in electric actuators. Theses losses consist of resistive electrical losses and mechanical friction losses. When only taking into account the electrical losses for a simplified robotic manipulator, a convex reformulation has been derived previously [1]. In this paper we include the dynamic joint friction losses into the objective. This also implies that we have to include the dynamic joint friction into the robot equations of motion, which appear in the torque constraints. Both the resulting objective and torque constraints are non-convex. The present paper proposes an efficient sequential convex programming (SCP) approach to solve the resulting optimal control problem. A key step here is to decompose the non-convex functions involved as a difference of convex functions. Numerical simulations illustrate the fast convergence of the proposed method in only a few SCP iterations, confirming the efficiency of the proposed framework. This high efficiency allows for an efficient tool to investigate the trade off between time-optimality and energy-optimality.
利用序贯凸规划实现最小时间与能量损失权衡的机器人路径优化
本文主要研究机器人的时间-能量最优路径跟踪问题。这考虑了沿预定几何路径移动的问题,在运动时间和电动执行器的两个主要热能损失之间有最小的权衡。这些损耗包括电阻性电损耗和机械摩擦损耗。当仅考虑简化机器人机械臂的电损耗时,先前已经导出了一个凸重构公式[1]。在本文中,我们将动态关节摩擦损失纳入目标。这也意味着我们必须在机器人运动方程中包含动态关节摩擦,它出现在扭矩约束中。所得到的目标约束和扭矩约束都是非凸的。本文提出了一种有效的序列凸规划(SCP)方法来解决由此产生的最优控制问题。这里的关键步骤是将所涉及的非凸函数分解为凸函数的差。数值仿真结果表明,该方法只需几次SCP迭代即可快速收敛,验证了所提框架的有效性。这种高效率允许一个有效的工具来研究时间最优性和能量最优性之间的权衡。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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