Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Uncertainty-Aware Task Allocation for Distributed Autonomous Robots   This paper addresses task-allocation problems with uncertainty in situational
awareness for distributed autonomous robots (DARs). The uncertainty propagation
over a task-allocation process is done by using the Unscented transform that
uses the Sigma-Point sampling mechanism. It has great potential to be employed
for generic task-allocation schemes, in the sense that there is no need to
modify an existing task-allocation method that has been developed without
considering the uncertainty in the situational awareness. The proposed
framework was tested in a simulated environment where the decision-maker needs
to determine an optimal allocation of multiple locations assigned to multiple
mobile flying robots whose locations come as random variables of known mean and
covariance. The simulation result shows that the proposed stochastic task
allocation approach generates an assignment with 30% less overall cost than the
one without considering the uncertainty.

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The categories of this paper are: chem-ph
9
The categories of this paper are: nlin
22
The categories of this paper are: chao-dyn
6
The categories of this paper are: astro-ph
3
The categories of this paper are: physics
12
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: nucl-ex
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The categories of this paper are: atom-ph
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The categories of this paper are: bayes-an
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The categories of this paper are: econ
10
The categories of this paper are: q-bio
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The categories of this paper are: funct-an
13
The categories of this paper are: quant-ph
14
The categories of this paper are: math-ph
35
The categories of this paper are: mtrl-th