Time-optimal trajectory optimization of serial robotic manipulator with kinematic and dynamic limits based on improved particle swarm optimization

Effective motion control could achieve the accurate positioning and fast movement of industrial robotics to improve productivity significantly. Time-optimal trajectory optimization (TO) is a great concern in robotics, which efficiency by providing high-speed reasonable references controllers. In this study, new general time-optimal TO strategy, second-order continuous polynomial interpolation function (SCPIF) combined with particle swarm cosine-decreasing weight (CDW-PSO) subject kinematic dynamic limits, successfully optimizes time PUMA 560 serial manipulator. The SCPIF be used generate trajectories six joints joint space based on assigned positions intervals. CDW-PSO algorithm further search for optimal limits angular displacement, velocity, acceleration, jerk, torque Two numerical experiments are conducted illustrate generalization ability algorithm. advantage CDW would reflected comparing random (RW), constant (CW), linearly decreasing (LDW), respectively, each experiment. experimental results show that perform better than RW-PSO, CW-PSO, LDW-PSO algorithms terms convergence rate quality convergent solution. proposed strategy applied all types manipulators while optimized incorporated controllers actual due considering limits.