Novelty detection and 3D shape retrieval using superquadrics and multi-scale sampling for autonomous mobile robots

Paulo Drews, P. Núñez, R. Rocha, M. Campos, J. Dias

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

25 Scopus citations

Abstract

There are several applications for which it is important to both detect and communicate changes in data models. For instance, in some mobile robotics applications (e.g. surveillance) a robot needs to detect significant changes in the environment (e.g. a layout change) which it may achieve by comparing current data provided by its sensors with previously acquired data (e.g. map) of the environment. This often constitutes an extremely challenging task due to the large amounts of data that must be compared in real-time. This paper proposes a framework to detect, and represent changes through a compact model. The main steps of the procedure are: multi-scale sampling to reduce the computation burden; change detection based on Gaussian mixture models; fitting superquadrics to detected changes; and refinement and optimization using the split and merge paradigm. Experimental results in various real and simulated scenarios demonstrate the approach's feasibility and robustness with large datasets.

Original languageBritish English
Title of host publication2010 IEEE International Conference on Robotics and Automation, ICRA 2010
Pages3635-3640
Number of pages6
DOIs
StatePublished - 2010
Event2010 IEEE International Conference on Robotics and Automation, ICRA 2010 - Anchorage, AK, United States
Duration: 3 May 20107 May 2010

Publication series

NameProceedings - IEEE International Conference on Robotics and Automation
ISSN (Print)1050-4729

Conference

Conference2010 IEEE International Conference on Robotics and Automation, ICRA 2010
Country/TerritoryUnited States
CityAnchorage, AK
Period3/05/107/05/10

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