A Multi-Objective Optimization Model for Planning Unmanned Aerial Vehicle Cruise Route
The use of unmanned aerial vehicles (UAVs) was introduced to monitor a traffic situation and the respective cruise route optimization problem was given. Firstly, a multi-objective optimization model was proposed, which considered two scenarios: the first scenario was that there were enough UAVs to m...
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doaj-a80d17030e1745809beb4e7f28786a8f2020-11-25T03:24:07ZengSAGE PublishingInternational Journal of Advanced Robotic Systems1729-88142016-06-011310.5772/6416510.5772_64165A Multi-Objective Optimization Model for Planning Unmanned Aerial Vehicle Cruise RouteXiaofeng Liu0Limei Gao1Zhiwei Guan2Yuqing Song3Rui Zhang4 School of Transportation and Automotive, Tianjin University of Technology and Education, Tianjin, China Traffic Science Research Institution of Tianjin City, Tianjin, China School of Transportation and Automotive, Tianjin University of Technology and Education, Tianjin, China School of Transportation and Automotive, Tianjin University of Technology and Education, Tianjin, China School of Transportation and Automotive, Tianjin University of Technology and Education, Tianjin, ChinaThe use of unmanned aerial vehicles (UAVs) was introduced to monitor a traffic situation and the respective cruise route optimization problem was given. Firstly, a multi-objective optimization model was proposed, which considered two scenarios: the first scenario was that there were enough UAVs to monitor all the targets, while the second scenario was that only some targets could be monitored due to a lack of UAVs. A multi-objective evolutionary algorithm was subsequently proposed to plan the UAV cruise route. Next, a route planning experiment, using the Microdrones md4-1000 UAV, was conducted and a UAV route planning case was studied. The experiment showed that the UAV actual flight route was almost consistent with the planned route. The case study showed that, compared with the initial optimal solutions, the optimal total UAV cruise distance and the number of UAVs used in scenario 1 decreased by 41.65% and 40.00%, respectively. Meanwhile, the total UAV cruise distance and the number of targets monitored in scenario 2 reduced by 15.75% and increased by 27.27%, respectively. In addition, a comparison study with other algorithms was conducted, while the optimization results were also improved. This demonstrated that the proposed UAV cruise route planning model was effective.https://doi.org/10.5772/64165 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Xiaofeng Liu Limei Gao Zhiwei Guan Yuqing Song Rui Zhang |
spellingShingle |
Xiaofeng Liu Limei Gao Zhiwei Guan Yuqing Song Rui Zhang A Multi-Objective Optimization Model for Planning Unmanned Aerial Vehicle Cruise Route International Journal of Advanced Robotic Systems |
author_facet |
Xiaofeng Liu Limei Gao Zhiwei Guan Yuqing Song Rui Zhang |
author_sort |
Xiaofeng Liu |
title |
A Multi-Objective Optimization Model for Planning Unmanned Aerial Vehicle Cruise Route |
title_short |
A Multi-Objective Optimization Model for Planning Unmanned Aerial Vehicle Cruise Route |
title_full |
A Multi-Objective Optimization Model for Planning Unmanned Aerial Vehicle Cruise Route |
title_fullStr |
A Multi-Objective Optimization Model for Planning Unmanned Aerial Vehicle Cruise Route |
title_full_unstemmed |
A Multi-Objective Optimization Model for Planning Unmanned Aerial Vehicle Cruise Route |
title_sort |
multi-objective optimization model for planning unmanned aerial vehicle cruise route |
publisher |
SAGE Publishing |
series |
International Journal of Advanced Robotic Systems |
issn |
1729-8814 |
publishDate |
2016-06-01 |
description |
The use of unmanned aerial vehicles (UAVs) was introduced to monitor a traffic situation and the respective cruise route optimization problem was given. Firstly, a multi-objective optimization model was proposed, which considered two scenarios: the first scenario was that there were enough UAVs to monitor all the targets, while the second scenario was that only some targets could be monitored due to a lack of UAVs. A multi-objective evolutionary algorithm was subsequently proposed to plan the UAV cruise route. Next, a route planning experiment, using the Microdrones md4-1000 UAV, was conducted and a UAV route planning case was studied. The experiment showed that the UAV actual flight route was almost consistent with the planned route. The case study showed that, compared with the initial optimal solutions, the optimal total UAV cruise distance and the number of UAVs used in scenario 1 decreased by 41.65% and 40.00%, respectively. Meanwhile, the total UAV cruise distance and the number of targets monitored in scenario 2 reduced by 15.75% and increased by 27.27%, respectively. In addition, a comparison study with other algorithms was conducted, while the optimization results were also improved. This demonstrated that the proposed UAV cruise route planning model was effective. |
url |
https://doi.org/10.5772/64165 |
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