Fast, On-Line Learning of Globally Consistent Maps
Autonomous Robots
Combining Multimodal Sensory Input for Spatial Learning
ICANN '02 Proceedings of the International Conference on Artificial Neural Networks
Global localization and topological map-learning for robot navigation
ICSAB Proceedings of the seventh international conference on simulation of adaptive behavior on From animals to animats
Map-based navigation in mobile robots
Cognitive Systems Research
Using a mobile robot for cognitive mapping
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Spatial information extraction for cognitive mapping with a mobile robot
COSIT'07 Proceedings of the 8th international conference on Spatial information theory
Evolution of self-organised path formation in a swarm of robots
ANTS'10 Proceedings of the 7th international conference on Swarm intelligence
Transition cells for navigation and planning in an unknown environment
SAB'06 Proceedings of the 9th international conference on From Animals to Animats: simulation of Adaptive Behavior
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More is known of the navigation skills of mice and rats than of any other vertebrate. The discovery of place cells (cells whose firing rate correlates with the spatial position of the animal) in the rat's hippoc ampus has inspired various attempts to model these cells. This work presents one such model which has been optimized on simulated autonomous agents and implemented on a mobile robot which learns to navigate within its environment through exploration using vision as its main sensory modal ity. The artificial mouse robot aMouse, a mobile robot with active whiskers and omnidirectional vision, is presented as an ideal robotic platform to study rodent navigation. The visual field of the robot is similar to the large visual field of rats and mice, and its whisker system uses real rat whiskers for tex ture recognition. The paper suggests how tactile information from the active whisker array on the robot can be used as an additional sensory modality for the place cell model described earlier.