Learning metric-topological maps for indoor mobile robot navigation
Artificial Intelligence
The spatial semantic hierarchy
Artificial Intelligence
Learning View Graphs for Robot Navigation
Autonomous Robots - Special issue on autonomous agents
Territory formation in mobile robots
ICAL 2003 Proceedings of the eighth international conference on Artificial life
Neural Correlates of First-Person Perspective as One Constituent of Human Self-Consciousness
Journal of Cognitive Neuroscience
Navigation and Acquisition of Spatial Knowledge in a Virtual Maze
Journal of Cognitive Neuroscience
Metric embedding of view-graphs
Autonomous Robots
IEEE Transactions on Neural Networks
The complementary roles of allostatic and contextual control systems in foraging tasks
SAB'10 Proceedings of the 11th international conference on Simulation of adaptive behavior: from animals to animats
Putting egocentric and allocentric into perspective
SC'10 Proceedings of the 7th international conference on Spatial cognition
A review of long-term memory in natural and synthetic systems
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
Mental travel primes place orientation in spatial recall
SC'12 Proceedings of the 2012 international conference on Spatial Cognition VIII
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In this paper, we sketch out a computational theory of spatial cognition motivated by navigational behaviours, ecological requirements, and neural mechanisms as identified in animals and man. Spatial cognition is considered in the context of a cognitive agent built around the action-perception cycle. Besides sensors and effectors, the agent comprises multiple memory structures including a working memory and a longterm memory stage. Spatial longterm memory is modelled along the graph approach, treating recognizable places or poses as nodes and navigational actions as links. Models of working memory and its interaction with reference memory are discussed. The model provides an overall framework of spatial cognition which can be adapted to model different levels of behavioural complexity as well as interactions between working and longterm memory. A number of design questions for building cognitive robots are derived from comparison with biological systems and discussed in the paper.