Cooperative Routing for an Air-Ground Vehicle Team-Exact Algorithm, Transformation Method, and Heuristics
This paper considers a cooperative vehicle routing problem for an intelligence, surveillance, and reconnaissance mission in the presence of communication constraints between the vehicles. The proposed framework uses a ground vehicle and an unmanned aerial vehicle (UAV) that travel cooperatively and...
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Veröffentlicht in: | IEEE transactions on automation science and engineering 2020-01, Vol.17 (1), p.537-547 |
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description | This paper considers a cooperative vehicle routing problem for an intelligence, surveillance, and reconnaissance mission in the presence of communication constraints between the vehicles. The proposed framework uses a ground vehicle and an unmanned aerial vehicle (UAV) that travel cooperatively and visit a set of targets while satisfying the communication constraints. The problem is formulated as a mixed-integer linear program, and a branch-and-cut algorithm is developed to solve the problem to optimality. Furthermore, a transformation method and a heuristic are also developed for the problem. The effectiveness of all the algorithms is corroborated through extensive computational experiments on several randomly generated instances. This paper is motivated by an intelligence, surveillance, and reconnaissance mission involving a single unmanned aerial vehicle (UAV) and a ground vehicle, where the vehicles must coordinate their activity in the presence of communication constraints. The combination of a small UAV and a ground vehicle is an ideal platform for such missions, since small UAVs can fly at low altitudes and can avoid obstacles or threats that would be problematic for the ground vehicle alone. This paper addresses the coordinated routing problem involving these two vehicles and presents an algorithm to obtain an optimal solution for this problem, fast heuristics to obtain good feasible solutions, and also a transformation method to transform any instance of this cooperative vehicle routing problem to an instance of the one-in-a-set traveling salesman problem. |
doi_str_mv | 10.1109/TASE.2019.2931894 |
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The proposed framework uses a ground vehicle and an unmanned aerial vehicle (UAV) that travel cooperatively and visit a set of targets while satisfying the communication constraints. The problem is formulated as a mixed-integer linear program, and a branch-and-cut algorithm is developed to solve the problem to optimality. Furthermore, a transformation method and a heuristic are also developed for the problem. The effectiveness of all the algorithms is corroborated through extensive computational experiments on several randomly generated instances. This paper is motivated by an intelligence, surveillance, and reconnaissance mission involving a single unmanned aerial vehicle (UAV) and a ground vehicle, where the vehicles must coordinate their activity in the presence of communication constraints. The combination of a small UAV and a ground vehicle is an ideal platform for such missions, since small UAVs can fly at low altitudes and can avoid obstacles or threats that would be problematic for the ground vehicle alone. This paper addresses the coordinated routing problem involving these two vehicles and presents an algorithm to obtain an optimal solution for this problem, fast heuristics to obtain good feasible solutions, and also a transformation method to transform any instance of this cooperative vehicle routing problem to an instance of the one-in-a-set traveling salesman problem.</description><identifier>ISSN: 1545-5955</identifier><identifier>EISSN: 1558-3783</identifier><identifier>DOI: 10.1109/TASE.2019.2931894</identifier><identifier>CODEN: ITASC7</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>ADVANCED PROPULSION SYSTEMS ; Algorithms ; Base stations ; Branch-and-cut ; Communication ; communication constraints ; cooperative vehicle routing ; Heuristic algorithms ; Heuristic methods ; heuristics ; Intelligence ; Land vehicles ; mixed-integer linear program ; Optimization ; path planning ; Reconnaissance ; Route planning ; Routing ; Surveillance ; Traffic surveillance ; Transformations ; Traveling salesman problem ; Unmanned aerial vehicles ; unmanned aerial vehicles (UAVs) ; Vehicle routing ; Vehicles</subject><ispartof>IEEE transactions on automation science and engineering, 2020-01, Vol.17 (1), p.537-547</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2020</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c363t-9bbf57e3a3e3f440c9da50b6f5937ed158c0668bc69b66e93b5ffb9e2f7da8e73</citedby><cites>FETCH-LOGICAL-c363t-9bbf57e3a3e3f440c9da50b6f5937ed158c0668bc69b66e93b5ffb9e2f7da8e73</cites><orcidid>0000-0002-6928-449X ; 000000026928449X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/8798870$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>230,314,780,784,796,885,27924,27925,54758</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/8798870$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc><backlink>$$Uhttps://www.osti.gov/servlets/purl/1835758$$D View this record in Osti.gov$$Hfree_for_read</backlink></links><search><creatorcontrib>Manyam, Satyanarayana G.</creatorcontrib><creatorcontrib>Sundar, Kaarthik</creatorcontrib><creatorcontrib>Casbeer, David W.</creatorcontrib><creatorcontrib>Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)</creatorcontrib><title>Cooperative Routing for an Air-Ground Vehicle Team-Exact Algorithm, Transformation Method, and Heuristics</title><title>IEEE transactions on automation science and engineering</title><addtitle>TASE</addtitle><description>This paper considers a cooperative vehicle routing problem for an intelligence, surveillance, and reconnaissance mission in the presence of communication constraints between the vehicles. The proposed framework uses a ground vehicle and an unmanned aerial vehicle (UAV) that travel cooperatively and visit a set of targets while satisfying the communication constraints. The problem is formulated as a mixed-integer linear program, and a branch-and-cut algorithm is developed to solve the problem to optimality. Furthermore, a transformation method and a heuristic are also developed for the problem. The effectiveness of all the algorithms is corroborated through extensive computational experiments on several randomly generated instances. This paper is motivated by an intelligence, surveillance, and reconnaissance mission involving a single unmanned aerial vehicle (UAV) and a ground vehicle, where the vehicles must coordinate their activity in the presence of communication constraints. The combination of a small UAV and a ground vehicle is an ideal platform for such missions, since small UAVs can fly at low altitudes and can avoid obstacles or threats that would be problematic for the ground vehicle alone. This paper addresses the coordinated routing problem involving these two vehicles and presents an algorithm to obtain an optimal solution for this problem, fast heuristics to obtain good feasible solutions, and also a transformation method to transform any instance of this cooperative vehicle routing problem to an instance of the one-in-a-set traveling salesman problem.</description><subject>ADVANCED PROPULSION SYSTEMS</subject><subject>Algorithms</subject><subject>Base stations</subject><subject>Branch-and-cut</subject><subject>Communication</subject><subject>communication constraints</subject><subject>cooperative vehicle routing</subject><subject>Heuristic algorithms</subject><subject>Heuristic methods</subject><subject>heuristics</subject><subject>Intelligence</subject><subject>Land vehicles</subject><subject>mixed-integer linear program</subject><subject>Optimization</subject><subject>path planning</subject><subject>Reconnaissance</subject><subject>Route planning</subject><subject>Routing</subject><subject>Surveillance</subject><subject>Traffic surveillance</subject><subject>Transformations</subject><subject>Traveling salesman problem</subject><subject>Unmanned aerial vehicles</subject><subject>unmanned aerial vehicles (UAVs)</subject><subject>Vehicle routing</subject><subject>Vehicles</subject><issn>1545-5955</issn><issn>1558-3783</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNo9kMFKAzEQhhdRUKsPIF6CXrs12WyyybGUWgVF0NVryGYnNqXd1CQr-vZuafE0c_j-f4Yvy64InhCC5V09fZtPCkzkpJCUCFkeZWeEMZHTStDj3V6ynEnGTrPzGFcYF6WQ-CxzM--3EHRy34BefZ9c94msD0h3aOpCvgi-71r0AUtn1oBq0Jt8_qNNQtP1pw8uLTdjVAfdxSG0GWp8h54hLX07Hipa9AB9cDE5Ey-yE6vXES4Pc5S938_r2UP-9LJ4nE2fckM5TblsGssqoJoCtWWJjWw1ww23TNIKWsKEwZyLxnDZcA6SNszaRkJhq1YLqOgou9n3-uGsisYlMEvjuw5MUkRQVjExQLd7aBv8Vw8xqZXvQzf8pQpKBaecYz5QZE-Z4GMMYNU2uI0Ov4pgtdOudtrVTrs6aB8y1_uMA4B_XlRSiArTP8r9fv4</recordid><startdate>202001</startdate><enddate>202001</enddate><creator>Manyam, Satyanarayana G.</creator><creator>Sundar, Kaarthik</creator><creator>Casbeer, David W.</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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subjects | ADVANCED PROPULSION SYSTEMS Algorithms Base stations Branch-and-cut Communication communication constraints cooperative vehicle routing Heuristic algorithms Heuristic methods heuristics Intelligence Land vehicles mixed-integer linear program Optimization path planning Reconnaissance Route planning Routing Surveillance Traffic surveillance Transformations Traveling salesman problem Unmanned aerial vehicles unmanned aerial vehicles (UAVs) Vehicle routing Vehicles |
title | Cooperative Routing for an Air-Ground Vehicle Team-Exact Algorithm, Transformation Method, and Heuristics |
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