典型文献
Velocity Constraints Based Approach for Online Trajectory Planning of High?Speed Parallel Robots
文献摘要:
High-speed parallel robots have been extensively utilized in the light industry. However, the influence of the nonlinear dynamic characteristics of high-speed parallel robots on system's dynamic response and stable operation cannot be ignored during the high-speed reciprocating motion. Thus, trajectory planning is essential for efficiency and stability from pick-and-place (PAP) actions. This paper presents a method for planning the equal-height pick-and-place trajec-tory considering velocity constraints to improve the PAP efficiency and stability of high-speed parallel robots. The velocity constraints in the start-and-end points can reduce vibration from picking and placing, making the trajectory more suitable to complex beltline situations. Based on velocity constraints, trajectory optimization includes trajectory smoothness and joint torque to optimize cycle time is carried out. This paper proposes an online trajectory optimiza-tion solution. By using back propagation (BP) neural networks, the solution is simplified and can be solved in real-time. Simulation and experiments were carried out on the SR4 parallel robot. The results show that the proposed method improves the efficiency, smoothness, and stability of the robot. This paper proposes an online trajectory planning method which is velocity constraints based and can improve the efficiency and stability of high-speed parallel robots. The work of this research is conducive to finely applying high-speed parallel robots.
文献关键词:
中图分类号:
作者姓名:
Di Yang;Fugui Xie;Xinjun Liu
作者机构:
State Key Laboratory of Tribology in Advanced Equipment,Department of Mechanical Engineering,Tsinghua University,Beijing 100084,China;Beijing Key Lab of Precision/Ultra?Precision Manufacturing Equipments and Control,Tsinghua University,Beijing 100084,China
文献出处:
引用格式:
[1]Di Yang;Fugui Xie;Xinjun Liu-.Velocity Constraints Based Approach for Online Trajectory Planning of High?Speed Parallel Robots)[J].中国机械工程学报,2022(06):415-426
A类:
beltline
B类:
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AB值:
0.497022
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