Time-Optimal Path Planning Model Using Genetic Algo- Rithm in RRR Robot

Abstract

The mathematical expression of the kinematic equations of each joint is utilized for the path planning using a quantic polynomial in joint space. In this study, a time optimization model for path planning using genetic algorithms with a vari- ety of crossover fraction and mutation rates is investigated. The optimization process is performed with MATLAB. Optimization using boundary conditions is performed with MATLAB. The result of the simulation, smooth speed graphs, angular position graphs, and the time when joint movements will complete the orbit as soon as possible are obtained. As a result of this study, a path planning model that can be applied to any robot is developed in joint space based on time optimization and can be used to shorten the task time, especially in task-based robots.