Planning Routes through uncertain territory
Artificial Intelligence
Mobile Robot Localization Using Sonar
IEEE Transactions on Pattern Analysis and Machine Intelligence
Visual map making for a mobile robot
Readings in computer vision: issues, problems, principles, and paradigms
Navigation and mapping in large-scale space
AI Magazine
Visual homing using an associative memory
Proceedings of a workshop on Image understanding workshop
Parallel distributed processing: explorations in the microstructure of cognition, vol. 1
Biologically plausible models of place recognition and goal location
Parallel distributed processing
Adaptive 3-D Object Recognition from Multiple Views
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special issue on interpretation of 3-D scenes—part II
A 3D world model builder with a mobile robot
International Journal of Robotics Research
Panoramic representation for route recognition by a mobile robot
International Journal of Computer Vision - Special issue on machine vision research at Osaka University
Model structuring and concept recognition: two aspects of learning for a mobile robot
IJCAI'83 Proceedings of the Eighth international joint conference on Artificial intelligence - Volume 2
LOGnets: a hybrid graph spatial representation for robot navigation
AAAI'90 Proceedings of the eighth National conference on Artificial intelligence - Volume 2
A Planning Map for Mobile Robots: Speed Control and Paths Finding in a Changing Environment
EWLR-8 Proceedings of the 8th European Workshop on Learning Robots: Advances in Robot Learning
Biologically inspired robot behavior engineering
The role of angularity in route choice: an analysis of motorcycle courier GPS traces
COSIT'09 Proceedings of the 9th international conference on Spatial information theory
Transition cells and neural fields for navigation and planning
IWINAC'05 Proceedings of the First international conference on Mechanisms, Symbols, and Models Underlying Cognition: interplay between natural and artificial computation - Volume Part I
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
Map-based navigation in mobile robots
Cognitive Systems Research
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We propose a real-time, view-based neurocomputational architecture for unsupervised 2-D mapping and localization within a 3-D environment defined by a spatially distributed set of visual landmarks. This architecture emulates place learning by hippocampal place cells in rats, and draws from anatomy of the primate object (''What'') and spatial (''Where'') processing streams. It extends by analogy, principles for learning characteristic views of 3-D objects (i.e., ''aspects''), to learning characteristic views of environments (i.e., ''places''). Places are defined by the identities and approximate poses (the What) of landmarks, as provided by visible landmark aspects. They are also defined by prototypical locations (the Where) within the landmark constellation, as indicated by the panoramic spatial distribution of landmark gaze directions. Combining these object and spatial definitions results in place nodes whose activity profiles define decision boundaries that parcel a 2-D area of the environment into place regions. These profiles resemble the spatial firing patterns over hippocampal place fields observed in rat experiments. A realtime demonstration of these capabilities on the binocular mobile robot MAVIN (the mobile adaptive visual navigator) illustrates the potential of this approach for qualitative mapping and fine localization.