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Continuous real time POMCP to find-and-follow people by a humanoid service robot

AuthorsGoldhoorn, Alex ; Garrell, Anaís ; Alquézar Mancho, Renato ; Sanfeliu, Alberto
Issue Date2014
PublisherInstitute of Electrical and Electronics Engineers
Citation14th IEEE-RAS International Conference on Humanoid Robots (Humanoids): 741-747 (2014)
AbstractThis study describes and evaluates two new methods for finding and following people in urban settings using a humanoid service robot: the Continuous Real-time POMCP method, and its improved extension called Adaptive Highest Belief Continuous Real-time POMCP follower. They are able to run in real-time, in large continuous environments. These methods make use of the online search algorithm Partially Observable Monte-Carlo Planning (POMCP), which in contrast to other previous approaches, can plan under uncertainty on large state spaces. We compare our new methods with a heuristic person follower and demonstrate that they obtain better results by testing them extensively in both simulated and real-life experiments. More than two hours, over 3 km, of autonomous navigation during real-life experiments have been done with a mobile humanoid robot in urban environments.
DescriptionTrabajo presentado al 14th IEEE-RAS International Conference on Humanoid Robots: Humanoids 2014 "Humans and Robots Face-to-Face", celebrado en Madrid (España) del 18 al 20 de noviembre de 2014.
Publisher version (URL)http://dx.doi.org/10.1109/HUMANOIDS.2014.7041445
Appears in Collections:(IRII) Comunicaciones congresos
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