Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Mixed Observable RRT: Multi-Agent Mission-Planning in Partially
  Observable Environments   This paper considers centralized mission-planning for a heterogeneous
multi-agent system with the aim of locating a hidden target. We propose a mixed
observable setting, consisting of a fully observable state-space and a
partially observable environment, using a hidden Markov model. First, we
construct rapidly exploring random trees (RRTs) to introduce the mixed
observable RRT for finding plausible mission plans giving way-points for each
agent. Leveraging this construction, we present a path-selection strategy based
on a dynamic programming approach, which accounts for the uncertainty from
partial observations and minimizes the expected cost. Finally, we combine the
high-level plan with model predictive control algorithms to evaluate the
approach on an experimental setup consisting of a quadruped robot and a drone.
It is shown that agents are able to make intelligent decisions to explore the
area efficiently and to locate the target through collaborative actions.

23
The categories of this paper are: solv-int
9
The categories of this paper are: nlin
2
The categories of this paper are: math
29
The categories of this paper are: funct-an
5
The categories of this paper are: gr-qc
18
The categories of this paper are: econ
37
The categories of this paper are: supr-con
6
The categories of this paper are: astro-ph
11
The categories of this paper are: hep-lat
13
The categories of this paper are: quant-ph
16
The categories of this paper are: stat
26
The categories of this paper are: bayes-an
12
The categories of this paper are: nucl-th
22
The categories of this paper are: chao-dyn
8
The categories of this paper are: hep-ex
28
The categories of this paper are: alg-geom