关键词: 工业机器人, 3-5-3多项式, 时间最优, 多策略改进粒子群算法

Abstract:  For the tasks of industrial robots finishing their work in the quickest possible time while meeting kinematics limitations， a time-optimal trajectory planning scheme was designed. Firstly， the robotic arms were modeled and analyzed， the kinematics equations were established. A 3-5-3 polynomial function was introduced as the research foundation of trajectory planning， and a time-optimal objective function was constructed under kinematics restrictions. Then， based on the improvement and optimization of the standard particle swarm optimization algorithm， a MIPSO algorithm was proposed by using tent chaotic mapping to initialize the population. Additionally， dynamically varying learning factors， nonlinearly decreasing modified inertia weights， and mutation operations in genetic algorithms were introduced. Finally， various algorithms were employed to optimize the robotic arms operating time， and the comparative results reveal that the MIPSO algorithm achieves a greater level of solution accuracy. The optimal time obtained from the solution is applied to the physical robotic arms， and the joint motion curves obtained are continuous without abrupt changes， which verifies the feasibility of the proposed scheme. 

Key words:  , industrial robot, 3-5-3 polynomial function, time-optimal, multi-strategy improved particle swarm optimization（MIPSO） algorithm