A model-based method for indoor mobile robot localization is presented herein; this method relies on monocular vision and uses straight-line correspondences. A classical four-step approach has been adopted (i.e. image acquisition, image feature extraction, image and model feature matching, and camer
Vision-based localization for mobile robots
✍ Scribed by Giovanni Adorni; Stefano Cagnoni; Stefan Enderle; Gerhard K. Kraetzschmar; Monica Mordonini; Michael Plagge; Marcus Ritter; Stefan Sablatnög; Andreas Zell
- Publisher
- Elsevier Science
- Year
- 2001
- Tongue
- English
- Weight
- 550 KB
- Volume
- 36
- Category
- Article
- ISSN
- 0921-8890
No coin nor oath required. For personal study only.
✦ Synopsis
Robust self-localization and repositioning strategies are essential capabilities for robots operating in highly dynamic environments. Environments are considered highly dynamic, if objects of interest move continuously and quickly, and if chances of hitting or getting hit by other robots are quite significant. An outstanding example for such an environment is provided by RoboCup.
Vision system designs for robots used in RoboCup are based on several approaches, aimed at fitting both the mechanical characteristics of the players and the strategies and operations that the different roles or playing situations may require. This paper reviews three approaches to vision-based self-localization used in the RoboCup middle-size league competition and describes the results they achieve in the robot soccer environment for which they have been designed.
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