Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: On the Empirical Evaluation of Information Gain Criteria for Active
  Action Selection   Accurate object pose estimation using multi-modal perception such as visual
and tactile sensing have been used for autonomous robotic manipulators in
literature. Due to variation in density of visual and tactile data, a novel
probabilistic Bayesian filter-based approach termed translation-invariant
Quaternion filter (TIQF) is proposed for pose estimation using point cloud
registration. Active tactile data collection is preferred by reasoning over
multiple potential actions for maximal expected information gain as tactile
data collection is time consuming. In this paper, we empirically evaluate
various information gain criteria for action selection in the context of object
pose estimation. We demonstrate the adaptability and effectiveness of our
proposed TIQF pose estimation approach with various information gain criteria.
We find similar performance in terms of pose accuracy with sparse measurements
($<15$ points) across all the selected criteria. Furthermore, we explore the
use of uncommon information theoretic criteria in the robotics domain for
action selection.

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The categories of this paper are: nlin
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The categories of this paper are: funct-an
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The categories of this paper are: q-alg
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The categories of this paper are: dg-ga
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The categories of this paper are: plasm-ph
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The categories of this paper are: nucl-th
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The categories of this paper are: solv-int
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The categories of this paper are: comp-gas
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The categories of this paper are: hep-ex
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The categories of this paper are: supr-con
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The categories of this paper are: eess
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The categories of this paper are: math-ph
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The categories of this paper are: atom-ph
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The categories of this paper are: adap-org
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The categories of this paper are: quant-ph
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The categories of this paper are: cmp-lg