Real-Time Motion Control of a Humanoid Robot Using Deep Learning

Abstract

This paper discusses the research work done for controlling the humanoid robot manually using deep learning. For teaching, personal assistance, search and rescue humanoid robot are used. Controlling manually makes it to do any task without any explicitly programming. Existing technique for manually controlling the humanoid are heavily dependent on hardware and they are not cost efficient. This paper proposes a novel method for controlling the humanoid using a 2D camera. The image from the 2D camera is processed and skeleton of the human body is captured using deep learning. Then the skeleton is used to control the actuators present in the humanoid robot using image classifier and ROS. As a proof of concept the upper body of the humanoid robot is controlled in real time using this method.