Betke-Gurvits-IEEETransRobotAutom97

Betke-Gurvits-IEEETransRobotAutom97 - IEEE TRANSACTIONS ON...

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Unformatted text preview: IEEE TRANSACTIONS ON ROBOTICS AND AUTOMATION, VOL. 13, NO. 2, APRIL 1997 251 Mobile Robot Localization Using Landmarks Margrit Betke and Leonid Gurvits Abstract We describe an efficient method for localizing a mobile robot in an environment with landmarks. We assume that the robot can identify these landmarks and measure their bearings relative to each other. Given such noisy input, the algorithm estimates the robots position and orientation with respect to the map of the environment. The algorithm makes efficient use of our representation of the landmarks by complex numbers. The algorithm runs in time linear in the number of landmarks. We present results of simulations and propose how to use our method for robot navigation. Index Terms Landmark navigation, map algorithms, mobile robot localization, robotics, triangulation. I. INTRODUCTION W E DESCRIBE AN efficient algorithm for localizing a mobile robot in an environment with landmarks. The robot has sensors that both identify landmarks and measure their bearings relative to each other. Such sensor information is generally uncertain and contains noise. Given the positions of possibly misidentified landmarks on a 2-D map of the environment and noisy measurements of their bearings relative to each other, the algorithm estimates the robots position with respect to the map of the environment. The algorithm makes efficient use of the geometry of the problem; specifically, the representation of the landmarks by complex numbers. The algorithm runs in time linear in the number of landmarks. Results of simulations are presented that explore the strength of the algorithm. Why is mobile robot localization important? A robot cannot accurately execute its commands. As a mobile robot moves through its environment, its actual position and orientation always differs from the position and orientation that it is commanded to hold. Wheel slippage is a major source of error. The errors accumulate and the location uncertainty increases over time. Dead-reckoning is not sufficient to locate the robot. Therefore, sensory feedback is needed to locate the robot in its environment. Consider an autonomous agent, which could be a mobile robot or a human traveler, who uses a map to navigate through an environment that contains landmarks. The landmarks are Manuscript received June 23, 1994; revised April 27, 1995. The work of M. Betke was supported by NSF Grant ASC-9217041 and Siemens Corp. Research. This paper was recommended for publication by Associate Editor R. Chatila and Editor S. E. Salcudean upon evaluation of the reviewers comments. M. Betke was with the Laboratory for Computer Science, Massachusetts Institute of Technology, Cambridge, MA 02139 USA. She is now with the Institute for Advanced Computer Studies, University of Maryland, College Park, MD 20742 USA (e-mail: betke@umiacs.umd.edu)....
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Betke-Gurvits-IEEETransRobotAutom97 - IEEE TRANSACTIONS ON...

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