Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Methods for Combining and Representing Non-Contextual Autonomy Scores
  for Unmanned Aerial Systems   Measuring an overall autonomy score for a robotic system requires the
combination of a set of relevant aspects and features of the system that might
be measured in different units, qualitative, and/or discordant. In this paper,
we build upon an existing non-contextual autonomy framework that measures and
combines the Autonomy Level and the Component Performance of a system as
overall autonomy score. We examine several methods of combining features,
showing how some methods find different rankings of the same data, and we
employ the weighted product method to resolve this issue. Furthermore, we
introduce the non-contextual autonomy coordinate and represent the overall
autonomy of a system with an autonomy distance. We apply our method to a set of
seven Unmanned Aerial Systems (UAS) and obtain their absolute autonomy score as
well as their relative score with respect to the best system.

30
The categories of this paper are: q-alg
29
The categories of this paper are: funct-an
8
The categories of this paper are: hep-ex
4
The categories of this paper are: cond-mat
12
The categories of this paper are: nucl-th
13
The categories of this paper are: quant-ph
28
The categories of this paper are: alg-geom
24
The categories of this paper are: dg-ga
21
The categories of this paper are: adap-org
7
The categories of this paper are: hep-th
11
The categories of this paper are: hep-lat
19
The categories of this paper are: eess
32
The categories of this paper are: atom-ph
14
The categories of this paper are: math-ph
22
The categories of this paper are: chao-dyn
10
The categories of this paper are: q-bio