SIMULATION OF ROBOTS’ INVERSE KINEMATICS IN ENGINEERING EDUCATION: AN APPROACH BASED ON GENETIC ALGORITHMS

Abstract

The study of articulated robots necessarily goes through the development of their kinematic models. In turn, the kinematics of a robot can be described through its direct and inverse models. The inverse kinematic model, through which the state of the joints is obtained as a function of the desired position for the free end of the robot, is usually described algebraically. However, this representation is often difficult to obtain. Thus, while the exact determination of the inverse kinematic model is unquestionable, the use of genetic algorithms in the design stage can be very attractive because it allows predicting the behavior of the robot before the formal development of its model. In this sense, the results of this work present a relatively fast way to simulate the inverse kinematic model, which can be useful in teaching robotics in engineering, allowing the student to have a broader view of the model, coming to identify points that must be corrected or that can be optimized in the structure of a robot. It can be concluded that the use of genetic algorithms in robotics is feasible, having as main advantages its easy computational implementation and its precision in the representation of kinematic models.