Localization Methods for a Mobile Robot in Urban Environments
Year: 2004
Type: article
Abstract: This paper addresses the problems of building a functional mobile robot for urban site navigation and modeling with focus on keeping track of the robot location. We have developed a localization system that employs two methods. The first method uses odometry, a compass and tilt sensor, and a global positioning sensor. An extended Kalman filter integrates the sensor data and keeps track of the uncertainty associated with it. The second method is based on camera pose estimation. It is used when the uncertainty from the first method becomes very large. The pose estimation is done by matching linear features in the image with a simple and compact environmental model. We have demonstrated the functionality of the robot and the localization methods with real-world experiments.
Source: IEEE Transactions on Robotics
Authors: A. Georgiev, P.K. Allen
Institution: Columbia University
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2124768549