Application of artificial neural network for control and navigation of humanoid robot

With the development of science and technology, humanoid robots are widely used among several industries. Humanoid robots are seen as a human replacement in a vast sense. It is a test for analysts to imitate the human aptitude in a counterfeit humanoid robot movement framework. With the developing innovation, the humanoid robots are being created for planetary investigation alongside other versatile robots to additionally enhance the mobility in a thickened domain. This paper is focussed on the development of an Artificial Neural Network based navigational controller for path planning examination of humanoid robot strolling. The path planning analysis is carried out on a NAO humanoid robot. Sensory information regarding obstacle distances and location of target are fed as inputs to the controller and required streaming angle is obtained as the output. Navigational analysis has been performed in both simulation and experimental environments with complicated arena conditions. Finally, a comparison between simulation and experimental results has been done, and the result are found to be in good agreement.