Trajectory Smoothing Planning of Delta Parallel Robot Combining Cartesian and Joint Space

反向动力学 弹道 平滑的 控制理论(社会学) 运动学 笛卡尔坐标系 计算机科学 机器人 机器人末端执行器 数学 人工智能 计算机视觉 几何学 物理 控制(管理) 经典力学 天文
作者
Dachang Zhu,Yizhu He,Xingxing Yu,Fangyi Li
出处
期刊:Mathematics [Multidisciplinary Digital Publishing Institute]
卷期号:11 (21): 4509-4509
标识
DOI:10.3390/math11214509
摘要

Delta parallel robots have been widely used in precision processing, handling, sorting, and the assembly of parts, and their high efficiency and motion stability are important indexes of their performance.Corners created by small line segments in trajectory planning cause abrupt changes in a tangential discontinuous trajectory, and the vibration and shock caused by such changes seriously affect the robot’s high-speed and high-precision performance. In this study, a trajectory-planning method combining Cartesian space and joint space is proposed. Firstly, the vector method and microelement integration method were used to establish the complete kinematic and dynamic equations of a delta parallel robot, and an inverse kinematic/dynamic model-solving program was written based on the MATLAB software R2020a. Secondly, the end-effector trajectory of the delta parallel robot was planned in Cartesian space, and the data points and inverse control points of the end effector’s trajectory were obtained using the normalization method. Finally, the data points and control points were mapped to the joint space through the inverse kinematic equation, and the fifth-order B-spline curve was adopted for quadratic trajectory planning, which allowed the high-order continuous smoothing of the trajectory planning to be realized. The simulated and experimental results showed that the trajectory-smoothing performance in continuous high-order curvature changes could be improved with the proposed method. The peak trajectory tracking error was reduced by 10.53%, 41.18%, and 44.44%, respectively, and the peak torque change of the three joints was reduced by 3.5%, 11.6%, and 1.6%, respectively.
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