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Real-time computer vision system for mobile robot

The purpose of this paper is to present a real-time vision system for position determination and vision guidance to navigate an autonomous mobile robot in a known environment. We use a digital camera, which provides ten times the video capture bandwidth than a USB, using FireWire interface. In order to achieve real-time image processing we use MMX technology to accelerate vision tasks. Camera calibration is a necessary step in 3D computer vision in order to extract metric information from 2D images. Calibration is used to determine the camera parameters by minimizing the mean square error between model and calibration points. The camera calibration we use here is based on several views of a planar calibration pattern, which is an easy-to-use and accurate algorithm. For position pose of the robot we use the corner points and lines, features extracted from the image, and matched with the model of the environment. The algorithm is as follows: first we compute an initial pose using the Ganatipathy's four-point algorithm, and we use this initial estimation as the starting point for the iterative algorithm proposed by Araujo in order to refine our pose.