Vision based Object Recognition and Localization by a Network Connected Distributed Robotic Systems

Abstract

Object recognition and Localization is an important problem in computer vision and robotics. Advances in computer vision has resulted into many object recognition techniques but most of them are computationally very heavy and requires robot unit to have high processing systems. When it comes to small size embedded robotic systems, these techniques can not be applied because of the constraints of execution time. Here, a popular SURF based recognition technique is adopted and some of the important changes are addressed which make it possible to use it on small size robots with limited resources. A team of small robots are used which are given prior training to search for 2D and 3D objects of interest in the environment. For the localization of the robots and objects a new template, designed for passive markers based tracking, is introduced. These markers are placed on the top of each robot and they are tracked by the two ceiling mounted cameras. The information from ceiling mounted cameras and from the team of robots is used collectively to localize the object of interest in the environment.