{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,24]],"date-time":"2026-08-24T09:38:15Z","timestamp":1787564295401,"version":"build-2736575974"},"reference-count":25,"publisher":"Association for Computing Machinery (ACM)","issue":"10","license":[{"start":{"date-parts":[[2018,9,26]],"date-time":"2018-09-26T00:00:00Z","timestamp":1537920000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["Commun. ACM"],"published-print":{"date-parts":[[2018,9,26]]},"abstract":"<jats:p>\n                    Autonomous drones represent a new breed of mobile computing system. Compared to smartphones and connected cars that only opportunistically sense or communicate, drones allow motion control to become part of the application logic. The efficiency of their movements is largely dictated by the low-level control enabling their autonomous operation based on high-level inputs. Existing implementations of such low-level control operate in a time-triggered fashion. In contrast, we conceive a notion of reactive control that allows drones to execute the low-level control logic only upon recognizing\n                    <jats:italic>the need to<\/jats:italic>\n                    , based on the influence of the environment onto the drone operation. As a result, reactive control can\n                    <jats:italic>dynamically adapt<\/jats:italic>\n                    the control rate. This brings fundamental benefits, including more accurate motion control, extended lifetime, and better quality of service in end-user applications. Based on 260+ hours of real-world experiments using three aerial drones, three different control logic, and three hardware platforms, we demonstrate, for example, up to 41% improvements in motion accuracy and up to 22% improvements in flight time.\n                  <\/jats:p>","DOI":"10.1145\/3264417","type":"journal-article","created":{"date-parts":[[2018,9,26]],"date-time":"2018-09-26T12:25:19Z","timestamp":1537964719000},"page":"96-104","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":4,"title":["Fundamental concepts of reactive control for autonomous drones"],"prefix":"10.1145","volume":"61","author":[{"given":"Luca","family":"Mottola","sequence":"first","affiliation":[{"name":"Politecnico di Milano, Italy and SICS Swedish ICT"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kamin","family":"Whitehouse","sequence":"additional","affiliation":[{"name":"University of Virginia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2018,9,26]]},"reference":[{"key":"e_1_2_1_1_1","volume-title":"Analysis and Design of Nonlinear Control Systems","author":"\u00c5str\u00f6m K.J.","year":"2007"},{"key":"e_1_2_1_2_1","unstructured":"\u00c5str\u00f6m K.J. 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Filming sport events with mobile camera drones: Mathematical modeling and algorithms. goo.gl\/v7Qo80 2012. Technical report."},{"key":"e_1_2_1_18_1","unstructured":"Nex F. Remondino F. UAV for 3D mapping applications: A review. Applied Geomatics (2003).  Nex F. Remondino F. UAV for 3D mapping applications: A review. Applied Geomatics (2003)."},{"key":"e_1_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1145\/2935620.2935630"},{"key":"e_1_2_1_20_1","unstructured":"Pieps. ARVA Transceivers. goo.gl\/tPywra.  Pieps. 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