NDLI: Manipulation planning using model-based belief dynamics

Content Provider	IEEE Xplore Digital Library
Author	Sen, Shiraj Grupen, Roderic
Copyright Year	2013
Description	Author affiliation: Laboratory for Perceptual Robotics at the Department of Computer Science, University of Massachusetts Amherst, 01003, USA (Sen, Shiraj; Grupen, Roderic)
Abstract	Planning in partially-observable domains require an agent to fuse prior knowledge with observations to update belief and to search for optimal plans that reduce uncertainty with respect to the task. This requires a knowledge organization that captures the underlying dynamics of the belief space and its probabilistic dependency on actions. In this paper, we present a functional representation for organizing knowledge about the environment in terms of interaction statistics. The representation utilizes a uniform, domain-general description of state that applies to a wide variety of tasks. We show how a planning algorithm can exploit this knowledge representation to build plans directly in the space of control actions. Given incomplete state information, the planner interacts with the task to acquire the information required to solve it. We illustrate the approach in multiple demonstrations of an object recognition task.
Starting Page	403
Ending Page	409
File Size	1077460
Page Count	7
File Format	PDF
ISBN	9781479926176
ISSN	21640572
e-ISBN	9781479926190
DOI	10.1109/HUMANOIDS.2013.7030006
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-10-15
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Visualization Uncertainty Computational modeling Robot sensing systems Probabilistic logic Planning
Content Type	Text
Resource Type	Article

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