Optimal trajectory planning of industrial robot for improving positional accuracy

混蛋 弹道 控制理论(社会学) 加速度 扭矩 计算机科学 工业机器人 分类 运动规划 遗传算法 轨迹优化 MATLAB语言 数学优化 机器人 模拟 最优控制 数学 算法 人工智能 控制(管理) 物理 经典力学 热力学 操作系统 天文
作者
Amruta Rout,B. B. V. L. Deepak,Bibhuti Bhusan Biswal,Golak Bihari Mahanta
出处
期刊:Industrial Robot-an International Journal [Emerald Publishing Limited]
卷期号:48 (1): 71-83 被引量:9
标识
DOI:10.1108/ir-07-2019-0148
摘要

Purpose The purpose of this paper is to improve the positional accuracy, smoothness on motion and productivity of industrial robot through the proposed optimal joint trajectory planning method. Also a new improved algorithm, i.e. non-dominated sorting genetic algorithm-II (NSGA-II) with achievement scalarizing function (ASF) has been proposed to obtain better optimal results compared to previously used optimization methods. Design/methodology/approach The end effector positional errors can be reduced by limiting the uncertainties of dynamic parameter variations like torque rate of joints. The jerk induced in robot joints due to acceleration variations are need to be minimized which otherwise induces vibrations in the manipulator that causes deviation in the encoders. But these lead to a vast increase in total travel time which affects the cost function of trajectory planning. Therefore, these three objectives need to be minimized individually so that an optimal trajectory path can be achieved with minimum positional error. Findings The simulation results have been obtained by running the proposed hybrid NSGA-II with ASF in MATLAB R2017a software. The optimal time intervals have been used to calculate jerk, acceleration and torque values for consecutive points on the trajectory path. From the simulation and experimental results, it can be concluded that the optimization technique could be used effectively for the trajectory planning of six-axis industrial manipulator in the joint space on the basis of minimum time-jerk-torque rate criteria. Originality/value In this paper, a new approach based on hybrid multi-objective optimization technique by combining NSGA-II with ASF has been applied to find the minimal time-jerk- torque rate joint trajectory of a six-axis industrial robot for obtaining higher positional accuracy. The results obtained from the execution of algorithm have been validated through experimentation using Kawasaki RS06L industrial robot for a particular defined path.
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