A bayesian conceptualization of space for mobile robots

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A bayesian conceptualization of space for mobile robots
Abstract— The future of robots, as our companions is dependent on their ability to understand, interpret and represent the environment in a human compatible manner. Towards this aim of making robots more spatially cognizant, the presented work is part of an attempt to create a hierarchical probabilistic concept-oriented representation of space, based on objects. Specifically, this work details efforts taken towards learning and generating concepts from the perceived objects and attempts to classify places using the concepts gleaned. The approach is based on learning from exemplars, clustering and the use of Bayesian network classifiers. Experiments on conceptualization and place classification are reported. Thus, the theme of the work is - conceptualization and classification for representation and spatial cognition.
Shrihari Vasudevan, Roland Siegwart
Added 03 Jun 2010
Updated 03 Jun 2010
Type Conference
Year 2007
Where IROS
Authors Shrihari Vasudevan, Roland Siegwart
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