Abstract
This study proposes a trajectory planning technique for robots using 3-5-3 polynomial interpolation that is based on an enhanced second-order oscillatory particle swarm algorithm with kinematic constraints like as velocity, acceleration, and jerk. A kinematic analysis of a six-axis industrial robot is carried out, and for trajectory planning, a 3-5-3 polynomial interpolation function is developed. For the issues where the conventional particle swarm technique is prone to local search and local optimality, the improved second-order oscillatory particle swarm approach is proposed. The technique uses time-jerk as the search space to find the best robot trajectory. To guarantee that the robot runs as quickly and smoothly as feasible, any optimization objective that does not satisfy the kinematic restrictions is removed. Trajectory planning in MATLAB for a six-axis industrial robot in joint space demonstrates the algorithm's efficacy under kinematic constraints.
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