An Hyperincursive Method for the Solution of the Inverse Kinematics of Industrial Robots Based on Neural Networks and Genetic Algorithms

The robotic inverse kinematic problem can be rightly classified as a very felt theme in the field of robotics. Many studies have been carried out in order to find new methods for the solution of the problem as alternatives to the traditional ones. In particular, every method able to improve the calculation speed is more and more appreciated. In the present paper an innovative method for the numerical inversion of non linear equations sets is shown. The approach is based on some procedures typical of the soft-computing area. In particular, the inverse kinematic problem is solved by a Neural Network optimised by means of a Genetic Algorithm acting inside an Hyperincursive scheme. After the introduction of the methodology developed, the paper shows some results obtained on a SCARA robot; they appear very good in terms of computational speed, even if the solution precision is not high near the boundaries of the working area.