Self-organization and associative memory: 3rd edition
Self-organization and associative memory: 3rd edition
Mapbuilding using self-organising networks in “really useful robots”
Proceedings of the first international conference on simulation of adaptive behavior on From animals to animats
Navigating with a rat brain: a neurobiologically-inspired model for robot spatial representation
Proceedings of the first international conference on simulation of adaptive behavior on From animals to animats
Using Hippocampal `Plane Cells' for Navigation, Exploiting Phase Coding
Advances in Neural Information Processing Systems 5, [NIPS Conference]
A Robust Layered Control System For a Mobile Robot
A Robust Layered Control System For a Mobile Robot
Constructing maps for mobile robot navigation based on ultrasonic range data
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Spatial learning for navigation in dynamic environments
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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This paper presents an episodic mapping mechanism used for the self-localisation of autonomous mobile robots. A two layer self organising neural network classifies perceptual and episodic information to identify "perceptual landmarks" (and thus the robot's position in the world) uniquely. Through this process relevant information is obtained from the temporal flow of ambiguous and redundant sensory information, such that meaningful internal representations of the robot's environment emerge through an unsupervised process of self-organisation, constructing an analogy to the real world.