Control of singularity trajectory tracking for robotic manipulator by genetic algorithms

he search for optimization of mechanisms and systems is constant and quite desirable in several areas and, therefore, has been gaining more and more emphasis in scientific research. In this paper, two methods for solving singularities, which can occur while a robot arm is moving through a given trajectory, are presented in order to optimize the trajectory tracking control. One method is based on a local genetic algorithm and the other on a global genetic algorithm. Polynomial trajectories up to 3rd degree were used to evaluate the performance of each method by analyzing the trajectory error, number of singularities and computation cost. From the results, it can be concluded that the method based on the global genetic algorithm had the best performance, once it followed the 3rd degree trajectory with the lowest error, number of singularities and computation cost. The results presented are related to the simulation considering a 6-DOF robotic arm.