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Paper WeD08.6

Pronobis, Andrzej (Royal Institute of Technology), Jensfelt, Patric (KTH - Royal Institute of Technology)

Large-scale Semantic Mapping and Reasoning with Heterogeneous Modalities

Scheduled for presentation during the Regular Session "Visual Learning" (WeD08), Wednesday, May 16, 2012, 17:45−18:00, Meeting Room 8 (Wacipi)

2012 IEEE International Conference on Robotics and Automation, May 14-18, 2012, RiverCentre, Saint Paul, Minnesota, USA

This information is tentative and subject to change. Compiled on February 24, 2018

Keywords Recognition, Mapping, Service Robots

Abstract

This paper presents a probabilistic framework combining heterogeneous, uncertain, information such as object observations, shape, size, appearance of rooms and human input for semantic mapping. It abstracts multi-modal sensory information and integrates it with conceptual common-sense knowledge in a fully probabilistic fashion. It relies on the concept of spatial properties which make the semantic map more descriptive, and the system more scalable and better adapted for human interaction. A probabilistic graphical model, a chain-graph, is used to represent the conceptual information and perform spatial reasoning. Experimental results from online system tests in a large unstructured office environment highlight the system's ability to infer semantic room categories, predict existence of objects and values of other spatial properties as well as reason about unexplored space.

 

 

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