Evolutionary indirect approach to solving trajectory planning problem for industrial robots operating in workspaces with obstacles

• We introduce an indirect approach for trajectory planning using parallel population genetic algorithm.
• Collision-free path planning is discussed.
• Dynamic constraints are considered.
• The goal is to minimize the robot execution time.

In this paper, an indirect method for trajectory planning for industrial robots has been addressed using an evolutionary algorithm. The algorithm is divided into three stages: (1) The acquisition of Adjacent Configurations (AC) for Path Planning subjected to kinematics, geometric and obstacle avoidance constraints. (2) The acquisition of a collision-free path between initial and goal robot configurations. This path consists of a set of ACs, and (3) The acquisition of a temporal history of the evolution for the robot joint coordinates, by minimizing the required time subjected to actuator limits. This algorithm has been evaluated by comparing the results with the direct procedures proposed by Rubio articles in 2009 and 2010.