基于五次NURBS的机械臂多目标轨迹优化规划

X. Shi, H. Fang, Lijie Guo
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引用次数: 17

摘要

提出了一种基于五次非均匀有理b样条(NURBS)的插值方法,以时间最优、能量最优和平滑度最优三个目标来构造机器人轨迹规划中的曲线。建立了五次NURBS曲线的数学模型,以获得端点构型参数可指定的高阶连续轨迹,并采用快速精英多目标遗传算法(NSGA-II)对机器人轨迹进行优化,以期得到这三个目标下的一系列Pareto最优解。通过对六自由度机器人的仿真表明,五次NURBS曲线可以得到高阶连续轨迹,NSGA-II算法可以为获得五次NURBS曲线的完美Pareto解提供一种有效的方法。通过构造平均模糊隶属函数,从Pareto最优集中选择一个潜在最优解,从而得到高阶连续最优轨迹。
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Multi-objective optimal trajectory planning of manipulators based on quintic NURBS
In this paper an interpolation method based on quintic non-uniform rational B-spline(NURBS) is proposed to construct curves when to plan the trajectory of manipulators with respect to three objectives, time optimal, energy optimal and smoothness optimal. The mathematical model of quintic NURBS curve is set up to gain high-order continuous trajectories with endpoint configuration parameters can be specified, and a fast and elitist multi-objective genetic algorithm (NSGA-II) is adopted to optimize the trajectory of manipulators aims to get a series of Pareto optimal solutions under the three objectives. Through the simulation with six-degree of freedom robot shows that quintic NURBS curve can get high-order continuous trajectories and NSGA-II algorithm can provide an effective approach to get the perfect Pareto solutions for quintic NURBS curve. By constructing a average fuzzy membership function, a potential optimal solution can be selected from Pareto optimal set, then the high-order continuous optimal trajectory can be obtained.
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