{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,8]],"date-time":"2026-07-08T15:51:03Z","timestamp":1783525863194,"version":"3.55.0"},"reference-count":48,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2019,8,30]],"date-time":"2019-08-30T00:00:00Z","timestamp":1567123200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Using unmanned robotic systems in military operations such as reconnaissance or surveillance, as well as in many civil applications, is common practice. In this article, the problem of monitoring the specified area of interest by a fleet of unmanned aerial systems is examined. The monitoring is planned via the Cooperative Aerial Model, which deploys a number of waypoints in the area; these waypoints are visited successively by unmanned systems. The original model proposed in the past assumed that the area to be explored is perfectly flat. A new formulation of this model is introduced in this article so that the model can be used in a complex environment with uneven terrain and\/or with many obstacles, which may occlude some parts of the area of interest. The optimization algorithm based on the simulated annealing principles is proposed for positioning of waypoints to cover as large an area as possible. A set of scenarios has been designed to verify and evaluate the proposed approach. The key experiments are aimed at finding the minimum number of waypoints needed to explore at least the minimum requested portion of the area. Furthermore, the results are compared to the algorithm based on the lawnmower pattern.<\/jats:p>","DOI":"10.3390\/s19173754","type":"journal-article","created":{"date-parts":[[2019,8,30]],"date-time":"2019-08-30T10:31:17Z","timestamp":1567161077000},"page":"3754","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":33,"title":["Cooperative Unmanned Aerial System Reconnaissance in a Complex Urban Environment and Uneven Terrain"],"prefix":"10.3390","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2251-8711","authenticated-orcid":false,"given":"Petr","family":"Stodola","sequence":"first","affiliation":[{"name":"Department of Intelligence Support, University of Defence, 66210 Brno, Czech Republic"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3257-0473","authenticated-orcid":false,"given":"Jan","family":"Drozd","sequence":"additional","affiliation":[{"name":"Department of Tactics, University of Defence, 66210 Brno, Czech Republic"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jan","family":"Mazal","sequence":"additional","affiliation":[{"name":"NATO Modelling &amp; Simulation Centre of Excellence, Doctrine, Education &amp; Training Branch, 00143 Roma, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jan","family":"Hodick\u00fd","sequence":"additional","affiliation":[{"name":"Department of Aircraft Technology, University of Defence, 66210 Brno, Czech Republic"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6601-0012","authenticated-orcid":false,"given":"Dalibor","family":"Proch\u00e1zka","sequence":"additional","affiliation":[{"name":"Centre for Security and Military Strategic Studies, University of Defence, 66210 Brno, Czech Republic"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2019,8,30]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Stodola, P., and Mazal, J. 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