Fast Laser Scan Matching using Polar Coordinates
International Journal of Robotics Research
IbPRIA '07 Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part I
Stereo vision specific models for particle filter-based SLAM
Robotics and Autonomous Systems
Global indoor self-localization based on the ambient magnetic field
Robotics and Autonomous Systems
Probabilistic multi-component extended strong tracking filter for mobile robot global localization
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
A global self-localization technique utilizing local anomalies of the ambient magnetic field
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Omnivision-based KLD-Monte Carlo Localization
Robotics and Autonomous Systems
A nonparametric learning approach to range sensing from omnidirectional vision
Robotics and Autonomous Systems
Two novel real-time local visual features for omnidirectional vision
Pattern Recognition
A global localization approach based on Line-segment Relation Matching technique
Robotics and Autonomous Systems
Journal of Intelligent and Robotic Systems
Scale Invariant Feature Transform on the Sphere: Theory and Applications
International Journal of Computer Vision
Robotics and Autonomous Systems
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The localization problem for an autonomous robot moving in a known environment is a well-studied problem which has seen many elegant solutions. Robot localization in a dynamic environment populated by several moving obstacles, however, is still a challenge for research. In this paper, we use an omnidirectional camera mounted on a mobile robot to perform a sort of scan matching. The omnidirectional vision system finds the distances of the closest color transitions in the environment, mimicking the way laser rangefinders detect the closest obstacles. The similarity of our sensor with classical rangefinders allows the use of practically unmodified Monte Carlo algorithms, with the additional advantage of being able to easily detect occlusions caused by moving obstacles. The proposed system was initially implemented in the RoboCup Middle-Size domain, but the experiments we present in this paper prove it to be valid in a general indoor environment with natural color transitions. We present localization experiments both in the RoboCup environment and in an unmodified office environment. In addition, we assessed the robustness of the system to sensor occlusions caused by other moving robots. The localization system runs in real-time on low-cost hardware.