Neural networks and natural intelligence
Neural networks and natural intelligence
Self-organization and associative memory: 3rd edition
Self-organization and associative memory: 3rd edition
Mobile Robotics: A Practical Introduction: History, Design, Analysis and Examples
Mobile Robotics: A Practical Introduction: History, Design, Analysis and Examples
Constructing maps for mobile robot navigation based on ultrasonic range data
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Bearing similarity measures for self-organizing feature maps
IDEAL'05 Proceedings of the 6th international conference on Intelligent Data Engineering and Automated Learning
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The ability to navigate is arguably the most fundamental competence of any mobile agent, besides the ability to avoid basic environmental hazards (e.g. obstacle avoidance). The simplest method to achieve navigation in mobile robot is to use path integration. However, because this method suffers from drift errors, it is not robust enough for navigation over middle scale and large scale distances. This paper gives an overview of research in mobile robot navigation at Manchester University, using mechanisms of self-organisation (artificial neuralnet works) to identify perceptuall and marks in the robot's environment, and to use such landmarks for route learning and self-localisation, as well as the quantitative assessment of the performance of such systems.