Cognitively Adequate Topological Robot Localization and Mapping

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Title: Cognitively Adequate Topological Robot Localization and Mapping
Authors: Corcoran, Padraig
Bertolotto, Michela
Leonard, John J.
Permanent link: http://hdl.handle.net/10197/6126
Date: Nov-2014
Abstract: Simultaneous Localization and Mapping (SLAM) is a fundamental problem in the eld of robotics which concerns mapping an environment or space while simultaneously localizing within this map. Given that one of the major goals of robotics is to perform tasks commonly performed by humans, we argue that SLAM methods should be cognitively adequate; that is, they should model the same properties of a space as the human cognition models. Topological properties are considered the most fundamental of those modlelled by the human cognition. Therefore in order to achieve cognitive adequacy such properties must be modelled explicitly. Research in the domain of spatial cognition has demonstrated that the topological properties modelled by the human cognition can be quanti ed using the Egenhofer Nine-Intersection Model (9-IM). In this work we propose a conceptual SLAM method which models the same properties as the 9-IM. Relative to existing topological SLAM methods, which model a single topological property of connectivity between locations, this method achieves a stronger degree of cognitive adequacy.
Type of material: Conference Publication
Publisher: ACM
Copyright (published version): 2014 ACM
Keywords: RoboticsLocalizationMappingNine-Intersection Model
DOI: 10.1145/2676528.2676534
Language: en
Status of Item: Peer reviewed
Conference Details: 22nd ACM SIGSPATIAL International Workshop on Indoor Spatial Awareness (ISA), Dallas, Texas, USA, 4-7 November, 2014
Appears in Collections:Computer Science Research Collection

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