REVOLUTIONIZING 3D ROBOTICS SMART CONTROL WITH NEURAL NETWORKS (Atena Editora)

Abstract

Given these difficulties, the objective of this work is to present a possible solution to this problem through the application of an artificial neural network (ANN) in a robotic arm with 4 degrees of freedom in three dimensions. The results found demonstrate the feasibility of the proposed solution in comparison with traditional geometric techniques. The use of ANNs offers a robust method for solving inverse kinematics, providing a viable alternative to conventional approaches. This technique simplifies the complexity associated with high degrees of freedom and efficiently manages the multiple solution problem. The findings indicate that ANNs can effectively deal with the complexities of inverse kinematics, paving the way for future advances in robotic control systems. By taking advantage of the learning capabilities of ANNs, this approach shows promise for improving the control accuracy and efficiency of robotic manipulators, contributing to more sophisticated and adaptable robotic applications. And finally, the work ends with a conclusion and suggestion for future work.