A REAL TIME GESTURE RECOGNITION SYSTEM FOR MOBILE ROBOTS

Abstract

This paper presents a vision system to be embedded in a mobile robot, both of them implemented using reconfigurable computing technology. The vision system captures gestures by means of a digital color camera, and then performs some pre-processing steps in order to use the image as input to a RAM-based neural network. The set of recognized gestures can be defined using the system on-chip training capabilities. All the above functionality has been implemented in a single FPGA chip. Experimental results have shown the system to be robust, with enough performance to meet real-time constraints (30 fps), and also high efficiency in the recognition process (true recognition rate of 99.57%).