Evolutionary Path Planning for Industrial Robot Using Intelligent Technique

Robot manipulators are programmable mechanical system designed to execute a great variety of tasks in repetitive way.In industrial environment, while productivity increases, cause reduction associated with robotic operation and maintenance can be obtained as a result of decreasing the values of dynamic quantities such as torque and jerk, with respect to a specific task. Furthermore,this procedure allows the execution of various tasks that require maximum system performance. By including obstacles avoidance ability to the robot skills, It is possible to improve the robot versatility, i.e., the robot can be used in a variety of operation conditions. In the present contribution, a study concerning the dynamic characteristics of serial robot manipulators is presented. An optimization strategy that considers the obstacle avoidance ability together with the dynamic performance associated with movement of robot is proposed. It results an optimal path planning strategy for a serial manipulator over time varying constrains in the robot workspace. This is achieved by using multi criteria optimization methods and optimal control techniques (NSGA-II). Numerical simulation results illustrate the interest of the proposed methodology and the present techniques can be useful for the design of robot controllers. A comprehensive user-friendly general-purpose software package has been developed using VC++ to obtain the optimal solutions using the proposed algorithms.