Author:
Naruse Keitaro, ,Fukui Shigekazu,Luo Jie
Abstract
The objective of this paper is to develop a localization systemof cooperativemultiple mobile robots, in which each robot is assumed to observe a set of known landmarks and equipped with an omnidirectional camera. In this paper, it is assumed that a robot can detect other robots by using the omnidirectional camera, share its estimated position with others, and utilize shared positions for its localization. In other words, each robot can be viewed as an additional mobile landmark to a set of stationary landmarks. A foremost concern is how well this system performs localization under a limited amount of information. This paper presents an investigation of self localization error of each robot in a group using Extended Kalman Filter to solve the localization problem with the insufficient landmarks and inaccurate position information.
Publisher
Fuji Technology Press Ltd.
Subject
Artificial Intelligence,Computer Vision and Pattern Recognition,Human-Computer Interaction
Reference10 articles.
1. S. Thrun, W. Burgard, and D. Fox, “Probabilistic Robotics,” pp. 189-215, 2006.
2. G. Welch and G. Bishop, “An Introduction to the Kalman Filter,” University of North Carolina at Chapel Hill, 2006.
3. L. E. Parker, “Current state of the art in distributed autonomous mobile robotics,” Proc. of the 5th Int. Symposium on Distributed Autonomous Robotic Systems (DARS 2000), Knoxville, TN, Oct. 4-6, pp. 3-12, 2000.
4. C. Ferrari, E. Pagello, J. Ota, and T. Arai, “Multirobot motion coordination in space and time,” Robotic Autonomous Systems, Vol.25, No.3/4, pp. 219-229, 1998.
5. D. Fox, W. Burgard, H. Kruppa, and S. Thrun, “Collaborative Multi-Robot Localization,” Proc. of German Conference on Artificial Intelligence (KI), Germany, 1999.
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