Representing and acquiring geographic knowledge
Representing and acquiring geographic knowledge
Structuring Free Space as a Hypergraph for Roving Robot Path Planning and Navigation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Towards a computational theory of cognitive maps
Artificial Intelligence
Blanche: position estimation for an autonomous robot vehicle
Autonomous robot vehicles
Qualitative navigation for mobile robots
Artificial Intelligence
Panoramic representation for route recognition by a mobile robot
International Journal of Computer Vision - Special issue on machine vision research at Osaka University
Memorizing and representing route scenes
Proceedings of the second international conference on From animals to animats 2 : simulation of adaptive behavior: simulation of adaptive behavior
Cognitive maps for mobile robots: a representation for mapping and navigation
Cognitive maps for mobile robots: a representation for mapping and navigation
Lazy Acquisition of Place Knowledge
Artificial Intelligence Review - Special issue on lazy learning
Learning metric-topological maps for indoor mobile robot navigation
Artificial Intelligence
Computing a representation of the local environment
Artificial Intelligence
The spatial semantic hierarchy
Artificial Intelligence
Neural Network Approaches to Cognitive Mapping
ANNES '95 Proceedings of the 2nd New Zealand Two-Stream International Conference on Artificial Neural Networks and Expert Systems
Vision: A Computational Investigation into the Human Representation and Processing of Visual Information
Spatial learning for navigation in dynamic environments
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Cognitive maps for mobile robots-an object based approach
Robotics and Autonomous Systems
Vision-based global localization for mobile robots with hybrid maps of objects and spatial layouts
Information Sciences: an International Journal
Using virtual scans for improved mapping and evaluation
Autonomous Robots
Interacting with Computers
Coarse-to-fine global localization for mobile robots with hybrid maps of objects and spatial layouts
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Using virtual scans to improve alignment performance in robot mapping
PerMIS '08 Proceedings of the 8th Workshop on Performance Metrics for Intelligent Systems
A hierarchical concept oriented representation for spatial cognition in mobile robots
50 years of artificial intelligence
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In this paper we examine the nature of theearly cognitive map – the beginnings of acognitive map formed from one's earlyimpressions of the environment one is in. Twodistinct paradigms have emerged from ourstudies of what information is initially identified in a cognitive map. The first, which weterm a space-based approach, emphasises makingexplicit the spatial extent of the currentlocal environment. The second emphasises makingexplicit the relationships between objects inthe local environment and we call this anobject-based approach. For both paradigms weexamine the psychological literature to findsupport for the approach and the roboticists'attempts at implementing the idea. We arguethat a space-based approach is the moreappropriate way to compute an early cognitivemap. In particular, we find that Siegel andWhite's (1975) object-based hypothesis, whichstates that the developmental progression of acognitive map is from landmark to route tosurvey map, is not supported. The space-basedparadigm underpins our own work in this areaand we outline our own space-based theory forcomputing an early cognitive map.