Position estimation techniques for an autonomous mobile robot: a review
Handbook of pattern recognition & computer vision
A Probabilistic Approach to Concurrent Mapping and Localization for Mobile Robots
Machine Learning - Special issue on learning in autonomous robots
RoboCup-97: Robot Soccer World Cup I
RoboCup-97: Robot Soccer World Cup I
A relative map approach to SLAM based on shift and rotation invariants
Robotics and Autonomous Systems
Probabilistic robot navigation in partially observable environments
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
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Due to their advantages, omni-directional mobile robots have found many applications especially in robotic soccer competitions. Despite recent advances, effective control and self-localization of omni-directional mobile robots remain as important and challenging issues. In this work, a practical approach for control and self-localization of an omni-directional robot is proposed. For this purpose, a simplified model of the system is derived for fast tuning of the control system parameters. In particular, strategies for fast tuning of PID/PD coefficients for position and orientation control are devised. A vision-based self-localization and the conventional odometry systems are fused for robust self-localization. The methods have been tested in the RoboCup competition field using three Persia middle size omni-directional robots. The experimental results are shown to demonstrate the effectiveness of the proposed system and its comparison with a few other compatible approaches.