An Investigation of Search Algorithms for Aerial Reconnaissance of an Area Target
Contributing USMA Research Unit(s)
Center for Innovation and Engineering, Civil and Mechanical Engineering, Mathematical Sciences
Proceedings of the 2022 General Donald R. Keith Memorial Capstone Conference
As drone technology becomes increasingly accessible in commercial and defense sectors, it is important to establish efficient ways of employing the technology to leverage its inherent advantages. In the context of a chemical, biological, radiological, and nuclear (CBRN) attack, an unmanned aerial system (UAS) can provide an understanding of the area affected by contaminants in a faster and safer way than a manned reconnaissance mission. Commonly used deterministic paths provide comprehensive coverage but they can require a substantial amount of time to reach each sector within a search space. The recently proposed Lissajous search pattern provides easily tunable parameters that can be adjusted according to the search space and anticipated size of the target. This paper provides an evaluation of Lissajous patterns against canonical search patterns and investigates ways of maximizing their efficiency for various target sizes.
4. Blankenship, R., Bluman, J. E. & Steckenrider, J. “An Investigation of Search Algorithms for Aerial Reconnaissance of an Area Target.” Proceedings of the 2022 General Donald R. Keith Memorial Capstone Conference, pp. 072-078. SISE. ISBN: 97819384962-2-6. http://www.ieworldconference.org/content/WP2022/Papers/18-GDRKMCC-22.pdf
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