CNLS '89 Proceedings of the ninth annual international conference of the Center for Nonlinear Studies on Self-organizing, Collective, and Cooperative Phenomena in Natural and Artificial Computing Networks on Emergent computation
Learning to Perceive and Act by Trial and Error
Machine Learning
Pattern matching algorithms
RoboCop: today and tomorrow-what we have learned
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Grounded Symbolic Communication between Heterogeneous Cooperating Robots
Autonomous Robots
A Framework for Robust Sensing in Multi-agent Systems
RoboCup 2001: Robot Soccer World Cup V
Anchoring Symbols to Sensor Data: Preliminary Report
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
The Body, the Mind or the Eye, First?
RoboCup-99: Robot Soccer World Cup III
Perceptual anchoring of symbols for action
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 1
A survey of fuzzy clustering algorithms for pattern recognition. II
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Biological and cognitive foundations of intelligent sensor fusion
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
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Robotic systems that carry out inferential activities over symbolic representations require a process that keeps a connection between physical objects and their symbolic image. Typically, this problem has been faced with ad-hoc solutions hardwired in the code. Recently, Coradeschi and Saffiotti have formalized this problem and they have called it anchoring. We propose a symbolic modelling approach to deal with the anchoring problem, in applications involving several embodied agents, by applying standard AI techniques. We discuss how such a modelling approach supports the process of instantiation of concepts by aggregating percepts possibly affected by imprecision and uncertainty. Percepts may come from several sensors possibly distributed both in the environment and on several mobile agents. Furthermore, we show how a tracking model can be used to maintain the link between percepts and conceptual instances in time. This approach to the anchoring problem has been implemented in a software module called MAP (MAP Anchors Perceptions), that has been tested in a robotic soccer application.