Velocity Constraints Based Approach for Online Trajectory Planning of High-Speed Parallel Robots

Abstract

Abstract 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 trajectory 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 optimization 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.

Keywords

• Trajectory planning
• High-speed parallel robot
• Velocity constraints
• BP neural network