Learning Navigational Maps by Observing Human Motion Patterns

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dc.contributor.author O'Callaghan, Simon en_US
dc.contributor.author Singh, Surya en_US
dc.contributor.author Alempijevic, Alen en_US
dc.contributor.author Ramos, Fabio en_US
dc.contributor.editor Bicchi, A; en_US
dc.date.accessioned 2012-10-12T03:36:22Z
dc.date.available 2012-10-12T03:36:22Z
dc.date.issued 2011 en_US
dc.identifier 2010005261 en_US
dc.identifier.citation O'Callaghan Simon et al. 2011, 'Learning Navigational Maps by Observing Human Motion Patterns', , IEEE, China, , pp. 4333-4340. en_US
dc.identifier.issn 978-1-61284-386-5 en_US
dc.identifier.other E1 en_US
dc.identifier.uri http://hdl.handle.net/10453/19212
dc.description.abstract Abstract?Observing human motion patterns is informative for social robots that share the environment with people. This paper presents a methodology to allow a robot to navigate in a complex environment by observing pedestrian positional traces. A continuous probabilistic function is determined using Gaussian process learning and used to infer the direction a robot should take in different parts of the environment. The approach learns and filters noise in the data producing a smooth underlying function that yields more natural movements. Our method combines prior conventional planning strategies with most probable trajectories followed by people in a principled statistical manner, and adapts itself online as more observations become available. The use of learning methods are automatic and require minimal tuning as compared to potential fields or spline function regression. This approach is demonstrated testing in cluttered office and open forum environments using laser and vision sensing modalities. It yields paths that are similar to the expected human behaviour without any a priori knowledge of the environment or explicit programming. en_US
dc.language en_US
dc.publisher IEEE en_US
dc.relation.hasversion Accepted manuscript version en_US
dc.relation.isbasedon http://dx.doi.org/10.1109/ICRA.2011.5980478 en_US
dc.title Learning Navigational Maps by Observing Human Motion Patterns en_US
dc.parent IEEE International Conference on Robotics and Automation (ICRA'11) en_US
dc.journal.volume en_US
dc.journal.number en_US
dc.publocation China en_US
dc.identifier.startpage 4333 en_US
dc.identifier.endpage 4340 en_US
dc.cauo.name FEIT.Faculty of Engineering & Information Technology en_US
dc.conference Verified OK en_US
dc.for 080100 en_US
dc.personcode 0000070588 en_US
dc.personcode 0000065109 en_US
dc.personcode 996745 en_US
dc.personcode 0000070587 en_US
dc.percentage 100 en_US
dc.classification.name Artificial Intelligence and Image Processing en_US
dc.classification.type FOR-08 en_US
dc.edition en_US
dc.custom Robotics and Automation (ICRA), 2011 IEEE International Conference on en_US
dc.date.activity 20110509 en_US
dc.location.activity Shanghai, China en_US
dc.description.keywords Gaussian processes , Humans , Navigation , Robot sensing systems , Trajectory , Uncertainty en_US


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