Efficient Localization for Robot Soccer Using Pattern Matching
Thomas Whelan,Sonja Stüdli,John McDonald,Richard H. Middleton +3 more
- 17 Oct 2011
- pp 16-30
TL;DR: A new approach to localization in the SPL which relies primarily on the information contained within white field markings while being efficient enough to run in real time on board a Nao robot.
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Abstract: One of the biggest challenges in the RoboCup Soccer Standard Platform League (SPL) is autonomously achieving and maintaining an accurate estimate of a robot’s position and orientation on the field. In other robotics applications many robust systems already exist for localization such as visual simultaneous localization and mapping (SLAM) and LIDAR based SLAM. These approaches either require special hardware or are very computationally expensive and are not suitable for the Nao robot, the current robot of choice for the SPL. Therefore novel approaches to localization in the RoboCup SPL environment are required. In this paper we present a new approach to localization in the SPL which relies primarily on the information contained within white field markings while being efficient enough to run in real time on board a Nao robot.
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Figures
Fig. 5. Sample Y Component Values at Point Surrounding ![Fig. 1. Standard Platform League Pitch Description [8].](/figures/fig-1-standard-platform-league-pitch-description-8-16vcqldv.png)
Fig. 1. Standard Platform League Pitch Description [8]. 
Fig. 4. Result of a Horizontal First Difference Operation Around a Point. 
Fig. 8. Localization System Test Results. 
Fig. 3. Example of Post Point Inclusion in MCA. 
Fig. 2. Example of the Modified Cox Algorithm.
![Fig. 1. Standard Platform League Pitch Description [8].](/figures/fig-1-standard-platform-league-pitch-description-8-16vcqldv.webp)
Citations
Multi-observation sensor resetting localization with ambiguous landmarks
Brian Coltin,Manuela Veloso +1 more
- 01 Oct 2013
TL;DR: This work introduces multi-observation sensor resetting (MOSR) to address the localization problem with sparse, ambiguous and noisy observations and demonstrates experimentally on the NAO humanoid robots that MOSR converges more efficiently to the robot’s true pose than standard sensorresetting, and is more robust to systematic vision errors.
•Journal Article
Particle-filter-based self-localization using landmarks and directed lines
TL;DR: In this article, the authors present a self-localization approach based on a particle filter that makes use of different features from the environment (beacons, goals, field lines, field wall) that provide different kinds of localization information and are recognized with different frequencies.
3
B-Human 2016 – Robust Approaches for Perception and State Estimation Under More Natural Conditions
Thomas Röfer,Tim Laue,Jesse Richter-Klug +2 more
- 30 Jun 2016
TL;DR: This paper presents multiple approaches to cope with the major rule changes of the RoboCup Standard Platform League, i.
2
References
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