NDLI: Inverse Reinforcement Learning algorithms and features for robot navigation in crowds: An experimental comparison

Content Provider	IEEE Xplore Digital Library
Author	Vasquez, D. Okal, B. Arras, K.O.
Copyright Year	2014
Description	Author affiliation: Soc. Robot. Lab., INRIA, Grenoble, France (Vasquez, D.) \|\| Social Robot. Lab., Univ. of Freiburg, Freiburg, Germany (Okal, B.; Arras, K.O.)
Abstract	For mobile robots which operate in human populated environments, modeling social interactions is key to understand and reproduce people's behavior. A promising approach to this end is Inverse Reinforcement Learning (IRL) as it allows to model the factors that motivate people's actions instead of the actions themselves. A crucial design choice in IRL is the selection of features that encode the agent's context. In related work, features are typically chosen ad hoc without systematic evaluation of the alternatives and their actual impact on the robot's task. In this paper, we introduce a new software framework to systematically investigate the effect features and learning algorithms used in the literature. We also present results for the task of socially compliant robot navigation in crowds, evaluating two different IRL approaches and several feature sets in large-scale simulations. The results are benchmarked according to a proposed set of objective and subjective performance metrics.
Starting Page	1341
Ending Page	1346
File Size	734073
Page Count	6
File Format	PDF
e-ISBN	9781479969340
DOI	10.1109/IROS.2014.6942731
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-09-14
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Navigation Vectors Robots Tin Silicon Vehicles Airports
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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