Intelligent Computational Scheme for Robot Inverse Kinematic Transformations

Abstract

This paper describes an intelligent computational scheme to obtain feasible solutions to the problem of inverse kinematics in robotics. The proposed scheme consists of a recurrent neural network and a knowledge-based (KB) system. The latter, based on the requirements and specifications of the robot task-space provided by the user, determines the neural network configuration and checks the robot link angles during the process of computation against the physical constraints. On the other hand, a recurrent neural network provides low-level computational features such as functional approximation, parallelism, learning and adaptation capabilities. The inverse kinematics problem in robotics involves the determination of joint variables for a desired end-effector position in the robot task-space. This problem is difficult in the sense that for a given end-effector position there can be many solutions, and some of these solutions may not be practically feasible due to the physical limitations imposed by the robot...