Time-optimal trajectory planning for a 6R jointed welding robot using adaptive genetic algorithms

Abstract

The trajectory of a revolute welding robot with six joints was planned in order to make the trajectory smooth and working time optimal. The time intervals between each point to be welded in Cartesian space were coded in binary, and the trajectory was implemented using an adaptive genetic algorithm while considering constraints of displacement, velocity, acceleration and jerk of each joint. According to the optimal time intervals generated, the results of simulation on robot kinematics show that the method designed for robot trajectory planning can obtain the goal trajectory. This method can solve the premature convergence and slow convergence problems, comparing with the simple genetic algorithm.