Motion Path Planning Optimization of a 4 DOF Robot Using Genetic Algorithm

Abstract

Recently due to limited resources and high cost of energy, optimization of energy consumption in many aspects is under study by researchers. The main purpose of this study is to optimize a robot with DOF to find the minimum energy consumption. At first, the kinematic, inverse kinematic and dynamic analysis of the robot is performed and then the energy equations of actuators are predicted. The default path of the robot is assumed as a five order polynomial and the consumption energy of the actuators for the motion of end-effector is obtained. For optimizing the path and comparing it to the default path, two random points in the workspace of the robot are selected and then five order spline in the robot workspace is defined. In addition, the continuity conditions are satisfied and the energy consumption for the new path is predicted. Finally, the genetic algorithm toolbox of MATLAB is applied for optimization. The energy function of the actuators are defined as the objective function and the workspace of the robot set as the guess range of spline points. Finally, the optimum path with minimum actuator energy consumption is obtained.