Optimization approaches for civil applications of unmanned aerial vehicles (UAVs) or aerial drones: A survey

By Alena Otto, Niels A. H. Agatz, James F. Campbell, Bruce L. Golden, Erwin Pesch. Networks, 2018

888 citations recorded by the source corpus.

Unmanned aerial vehicles (UAVs), or aerial drones, are an emerging technology with significant market potential. UAVs may lead to substantial cost savings in, for instance, monitoring of difficult‐to‐access infrastructure, spraying fields and performing surveillance in precision agriculture, as well as in deliveries of packages. In some applications, like disaster management, transport of medical supplies, or environmental monitoring, aerial drones may even help save lives. In this article, we provide a literature survey on optimization approaches to civil applications of UAVs. Our goal is to provide a fast point of entry into the topic for interested researchers and operations planning specialists. We describe the most promising aerial drone applications and outline characteristics of aerial drones relevant to operations planning. In this review of more than 200 articles, we provide insights into widespread and emerging modeling approaches. We conclude by suggesting promising directions for future research.

Subfields: Aerospace Engineering, Computer Vision and Pattern Recognition, Industrial and Manufacturing Engineering

View Paper: https://www.semanticscholar.org/paper/4f82fe0f8f7ed14cdbdeb28691cd4bc00ceed085

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Aerospace Engineering

  1. Matthias Winkenbach
  2. M. Moshref-Javadi
  3. Ines Khoufi
  4. Omar Cheikhrouhou
  5. Ritwik Raj
  6. Madhusanka Liyanage
  7. Shen Wang
  8. Chase C. Murray

In Computer Vision and Pattern Recognition

  1. Stefan Røpke
  2. David Sacramento
  3. David Pisinger
  4. Matthias Winkenbach
  5. M. Moshref-Javadi
  6. Tom Van Woensel
  7. Ritwik Raj
  8. Madhusanka Liyanage

In Industrial and Manufacturing Engineering

  1. Stefan Røpke
  2. Matthias Winkenbach
  3. M. Moshref-Javadi
  4. David Pisinger
  5. David Sacramento
  6. Tom Van Woensel
  7. Ines Khoufi
  8. Omar Cheikhrouhou

Citations in the corpus