Robot Location Estimation in the Situation Calculus

V. Belle, H. J. Levesque

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Location estimation is a fundamental sensing task in robotic applications, where the world is uncertain, and sensors and effectors are noisy. Most systems make various assumptions about the dependencies between state variables, and especially about how these dependencies change as a result of actions. Building on a general framework by Bacchus, Halpern and Levesque for reasoning about degrees of belief in the situation calculus, and a recent extension to it for continuous domains, in this paper we illustrate location estimation in the presence of a rich theory of actions using an example. We also show that while actions might affect prior distributions in nonstandard ways, suitable posterior beliefs are nonetheless entailed as a side-effect of the overall specification.
Original languageEnglish
Title of host publicationProceedings of the 1st Workshop on Planning and Robotics
Number of pages8
Publication statusPublished - 2013
Event23rd International Conference on Automated Planning and Scheduling - Rome, Italy
Duration: 10 Jun 201314 Jun 2013


Conference23rd International Conference on Automated Planning and Scheduling
Abbreviated titleICAPS 2013
Internet address

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