Robust Monte Carlo localization for mobile robots
Artificial Intelligence
Knowledge Representation, Reasoning, and Declarative Problem Solving
Knowledge Representation, Reasoning, and Declarative Problem Solving
Ad-hoc On-Demand Distance Vector Routing
WMCSA '99 Proceedings of the Second IEEE Workshop on Mobile Computer Systems and Applications
ACM SIGMOBILE Mobile Computing and Communications Review
ACM Computing Surveys (CSUR)
Managing Business Complexity: Discovering Strategic Solutions with Agent-Based Modeling and Simulation
Information fusion for wireless sensor networks: Methods, models, and classifications
ACM Computing Surveys (CSUR)
Engineering an Incremental ASP Solver
ICLP '08 Proceedings of the 24th International Conference on Logic Programming
Wireless Sensor and Actuator Networks: Technologies, Analysis and Design
Wireless Sensor and Actuator Networks: Technologies, Analysis and Design
Clasp: a conflict-driven answer set solver
LPNMR'07 Proceedings of the 9th international conference on Logic programming and nonmonotonic reasoning
GrinGo: a new grounder for answer set programming
LPNMR'07 Proceedings of the 9th international conference on Logic programming and nonmonotonic reasoning
Location tracking in a wireless sensor network by mobile agents and its data fusion strategies
IPSN'03 Proceedings of the 2nd international conference on Information processing in sensor networks
Fundamental limits of wideband localization: part I: a general framework
IEEE Transactions on Information Theory
Fundamental limits of wideband localization: part II: cooperative networks
IEEE Transactions on Information Theory
Annals of Mathematics and Artificial Intelligence
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Indoor position estimation constitutes a central task in home-based assisted living environments. Such environments often rely on a heterogeneous collection of low-cost sensors whose diversity and lack of precision has to be compensated by advanced techniques for localization and tracking. Although there are well established quantitative methods in robotics and neighboring fields for addressing these problems, they lack advanced knowledge representation and reasoning capacities. Such capabilities are not only useful in dealing with heterogeneous and incomplete information but moreover they allow for a better inclusion of semantic information and more general homecare and patient-related knowledge. We address this problem and investigate how state-of-the-art localization and tracking methods can be combined with Answer Set Programming, as a popular knowledge representation and reasoning formalism. We report upon a case-study and provide a first experimental evaluation of knowledge-based position estimation both in a simulated as well as in a real setting.