NDLI: Entropy-based strategies for physical exploration of the environment's degrees of freedom

Content Provider	IEEE Xplore Digital Library
Author	Otte, S. Kulick, J. Toussaint, M. Brock, O.
Copyright Year	2014
Description	Author affiliation: Robot. & Biol. Lab., Tech. Univ. Berlin, Berlin, Germany (Brock, O.) \|\| Machine Learning & Robot. Lab., Univ. Stuttgart, Stuttgart, Germany (Otte, S.; Kulick, J.; Toussaint, M.)
Abstract	Physical exploration refers to the challenge of autonomously discovering and learning how to manipulate the environment's degrees of freedom (DOF)-by identifying promising points of interaction and pushing or pulling object parts to reveal DOF and their properties. Recent existing work focused on sub-problems like estimating DOF parameters from given data. Here, we address the integrated problem, focusing on the higher-level strategy to iteratively decide on the next exploration point before applying motion generation methods to execute the explorative action and data analysis methods to interpret the feedback. We propose to decide on exploration points based on the expected information gain, or change in entropy in the robot's current belief (uncertain knowledge) about the DOF. To this end, we first define how we represent such a belief. This requires dealing with the fact that the robot initially does not know which random variables (which DOF, and depending on their type, which DOF properties) actually exist. We then propose methods to estimate the expected information gain for an exploratory action. We analyze these strategies in simple environments and evaluate them in combination with full motion planning and data analysis in a physical simulation environment.
Starting Page	615
Ending Page	622
File Size	1397262
Page Count	8
File Format	PDF
e-ISBN	9781479969340
DOI	10.1109/IROS.2014.6942623
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	Joints Entropy Robots Random variables Trajectory Uncertainty Friction
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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