Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Online Informative Path Planning for Active Classification Using UAVs   In this paper, we introduce an informative path planning (IPP) framework for
active classification using unmanned aerial vehicles (UAVs). Our algorithm uses
a combination of global viewpoint selection and evolutionary optimization to
refine the planned trajectory in continuous 3D space while satisfying dynamic
constraints. Our approach is evaluated on the application of weed detection for
precision agriculture. We model the presence of weeds on farmland using an
occupancy grid and generate adaptive plans according to information-theoretic
objectives, enabling the UAV to gather data efficiently. We validate our
approach in simulation by comparing against existing methods, and study the
effects of different planning strategies. Our results show that the proposed
algorithm builds maps with over 50% lower entropy compared to traditional
"lawnmower" coverage in the same amount of time. We demonstrate the planning
scheme on a multirotor platform with different artificial farmland set-ups.

25
The categories of this paper are: patt-sol
22
The categories of this paper are: chao-dyn
21
The categories of this paper are: adap-org
37
The categories of this paper are: supr-con
35
The categories of this paper are: mtrl-th
2
The categories of this paper are: math
26
The categories of this paper are: bayes-an
29
The categories of this paper are: funct-an
23
The categories of this paper are: solv-int
19
The categories of this paper are: eess
12
The categories of this paper are: nucl-th
36
The categories of this paper are: cmp-lg
17
The categories of this paper are: q-fin
5
The categories of this paper are: gr-qc
14
The categories of this paper are: math-ph
0
The categories of this paper are: hep-ph