Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A Cost-Effective Person-Following System for Assistive Unmanned Vehicles
  with Deep Learning at the Edge   The vital statistics of the last century highlight a sharp increment of the
average age of the world population with a consequent growth of the number of
older people. Service robotics applications have the potentiality to provide
systems and tools to support the autonomous and self-sufficient older adults in
their houses in everyday life, thereby avoiding the task of monitoring them
with third parties. In this context, we propose a cost-effective modular
solution to detect and follow a person in an indoor, domestic environment. We
exploited the latest advancements in deep learning optimization techniques, and
we compared different neural network accelerators to provide a robust and
flexible person-following system at the edge. Our proposed cost-effective and
power-efficient solution is fully-integrable with pre-existing navigation
stacks and creates the foundations for the development of fully-autonomous and
self-contained service robotics applications.

33
The categories of this paper are: plasm-ph
36
The categories of this paper are: cmp-lg
25
The categories of this paper are: patt-sol
6
The categories of this paper are: astro-ph
18
The categories of this paper are: econ
31
The categories of this paper are: ao-sci
30
The categories of this paper are: q-alg
10
The categories of this paper are: q-bio
22
The categories of this paper are: chao-dyn
2
The categories of this paper are: math
13
The categories of this paper are: quant-ph
12
The categories of this paper are: nucl-th
0
The categories of this paper are: hep-ph
7
The categories of this paper are: hep-th
20
The categories of this paper are: acc-phys
9
The categories of this paper are: nlin