Cognitive representation and Bayeisan model of spatial object contexts for robot localization

Authors:
Chuho Yi;Il Hong Suh;Gi Hyun Lim;Seungdo Jeong;Byung-Uk Choi
Affiliations:
Department of Electronics and Computer Engineering, Hanyang University, Seoul, Korea;Department of Electronics and Computer Engineering, Hanyang University, Seoul, Korea;Department of Electronics and Computer Engineering, Hanyang University, Seoul, Korea;Department of Electronics and Computer Engineering, Hanyang University, Seoul, Korea;Department of Electronics and Computer Engineering, Hanyang University, Seoul, Korea
Venue:
ICONIP'08 Proceedings of the 15th international conference on Advances in neuro-information processing - Volume Part I
Year:
2008

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Abstract

This paper proposes a cognitive representation and Bayesian model for spatial relations among objects that can be constructed with perception data acquired by a single consumer-grade camera. We first suggest a cognitive representation to be shared by humans and robots consisting of perceived objects and their spatial relations. We then develop Bayesian models to support our cognitive representation with which the location of a robot can be estimated sufficiently well to allow the robot to navigate in an indoor environment. Based on extensive localization experiments in an indoor environment, we show that our cognitive representation is valid in the sense that the localization accuracy improves whenever new objects and their spatial relations are detected and instantiated.