Determining Homogenous Transformation Matrix from DH Parameter Table using Deep Learning Techniques

One of the most popular ways of representing any robotic model mathematically is through Denavit-Hartenberg (DH) parameter table. And the most common way of finding a forward kinematics solution to any robotic model is by finding its homogenous transformation matrix, which is obtained from the DH parameter table by a certain set of steps or algorithms. In this research work, we have tried solving this problem in just a single step by deep learning method and thus finding forward kinematics of almost any kind of manipulator. This research work shows not just this problem but many more such complex problems which require a certain set of steps or algorithms that can be solved by deep learning techniques in a single step. The results obtained are very close to accurate and show the ability of deep learning techniques for solving different kinds of such problems.