An Improved Optimal Trajectory Planning Method of Six-axis Robotic Manipulators along Prescribed Path Constraints

Z. Xiong, Liping Chen, J. Ding
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Abstract

Optimal Control Problem (OCP) is a kind of classical problem with the state space equations, containing the optimal trajectory planning problem of robotic manipulators with complicated path constraints. The optimal control method (OCM) which contains direct and indirect methods is efficient to solve this kind of problems. The Pontryagin maximum principle is the core of the indirect method which includes tedious mathematical derivations, and is hard to work with the complex mechanical system. As the result, the direct methods represented by direct collocation method (DCM) are widely used in the engineering field. They transform the original optimal control problem to nonlinear programming problems (NLP), so that the general NLP solver can be used. There are mainly three different methods based on the above direct methods, including convex optimization (CO) methods, numerical integration (NI) methods and dynamic programming (DP) methods. This paper proposes a brand new idea which can streamline the problem description compared to the CO method, extend the general objective function compared to the NI method, and reduce the cost of storage compared to the DP method, and provides a feasible local optimal solution for the problem. In addition, the simulation experiment satisfies the kinodynamic constraints properly, and the validity of the proposed method is confirmed.
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一种改进的六轴机器人沿规定路径约束的最优轨迹规划方法
最优控制问题(OCP)是一类经典的状态空间方程问题,包含了具有复杂路径约束的机械臂最优轨迹规划问题。最优控制方法(OCM)是解决这类问题的有效方法,它包含了直接方法和间接方法。庞特里亚金极大值原理是间接方法的核心,间接方法的数学推导繁琐,难以处理复杂的机械系统。因此,以直接配点法(DCM)为代表的直接法在工程领域得到了广泛的应用。他们将原来的最优控制问题转化为非线性规划问题(NLP),从而可以使用一般的NLP求解器。在上述直接方法的基础上主要有三种不同的方法,即凸优化(CO)方法、数值积分(NI)方法和动态规划(DP)方法。本文提出了一种全新的思想,它比CO方法简化了问题描述,比NI方法扩展了一般目标函数,比DP方法减少了存储成本,并为问题提供了一个可行的局部最优解。仿真实验较好地满足了动力学约束,验证了所提方法的有效性。
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