Qualitative representation of positional information
Artificial Intelligence
Qualitative Representation of Spatial Knowledge
Qualitative Representation of Spatial Knowledge
COSIT '99 Proceedings of the International Conference on Spatial Information Theory: Cognitive and Computational Foundations of Geographic Information Science
Coarse Qualitative Descriptions in Robot Navigation
Spatial Cognition II, Integrating Abstract Theories, Empirical Studies, Formal Methods, and Practical Applications
Qualitative Velocity and Ball Interception
KI '02 Proceedings of the 25th Annual German Conference on AI: Advances in Artificial Intelligence
CCIA '02 Proceedings of the 5th Catalonian Conference on AI: Topics in Artificial Intelligence
Representing Spatial Activities by Spatially Contextualised Motion Patterns
RoboCup 2006: Robot Soccer World Cup X
Spatially Constrained Grammars for Mobile Intention Recognition
Proceedings of the international conference on Spatial Cognition VI: Learning, Reasoning, and Talking about Space
Reasoning with Qualitative Positional Information for Domestic Domains in the Situation Calculus
Journal of Intelligent and Robotic Systems
| Hi-index | 0.00 |
Since humans usually prefer to communicate in qualitative and not in quantitative categories, qualitative spatial representations are of great importance for user interfaces of systems that involve spatial tasks. Abstraction is the key for the generation of qualitative representations from observed data. This paper deals with the conversion of motion data into qualitative representations, and it presents a new generalization algorithm that abstracts from irrelevant details of a course of motion. In a further step of abstraction, the shape of a course of motion is used for qualitative representation. Our approach is motivated by findings of our own experimental research on the processing and representation of spatio-temporal information in the human visual system.