Distributed sensing units deploying on group unmanned vehicles
This study aims to use two unmanned vehicles (aerial vehicles and ground vehicles) to implement multi-machine cooperation to complete the assigned tasks quickly. Unmanned aerial/ground vehicles can call each other to send instant inquiry messages using the proposed cooperative communication protocol...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2021-07-01
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| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1177/15501477211036877 |
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| _version_ | 1832547850889723904 |
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| author | Bao Rong Chang Hsiu-Fen Tsai Jyong-Lin Lyu Chien-Feng Huang |
| author_facet | Bao Rong Chang Hsiu-Fen Tsai Jyong-Lin Lyu Chien-Feng Huang |
| author_sort | Bao Rong Chang |
| collection | DOAJ |
| description | This study aims to use two unmanned vehicles (aerial vehicles and ground vehicles) to implement multi-machine cooperation to complete the assigned tasks quickly. Unmanned aerial/ground vehicles can call each other to send instant inquiry messages using the proposed cooperative communication protocol to hand over the tasks between them and execute efficient three-dimensional collaborative operations in time. This study has demonstrated integrating unmanned aerial/ground vehicles into a group through the control platform (i.e. App operation interface) that uses the Internet of Things. Therefore, pilots can make decisions and communicate through App for cooperative coordination, allowing a group of unmanned aerial/ground vehicles to complete the tasks flexibly. In addition, the payload attached to unmanned air/ground vehicles can carry out multipurpose monitoring that implements face recognition, gas detection, thermal imaging, and video recording. During the experiment of unmanned aerial vehicle, unmanned aerial vehicle will plan the flight path and record the movement trajectory with global positioning system when it is on duty. As a result, the accuracy of the planned flight path achieved 86.89% on average. |
| format | Article |
| id | doaj-art-78850fac97c0429e90bdd6b3d132edcb |
| institution | Kabale University |
| issn | 1550-1477 |
| language | English |
| publishDate | 2021-07-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Distributed Sensor Networks |
| spelling | doaj-art-78850fac97c0429e90bdd6b3d132edcb2025-02-03T06:43:15ZengWileyInternational Journal of Distributed Sensor Networks1550-14772021-07-011710.1177/15501477211036877Distributed sensing units deploying on group unmanned vehiclesBao Rong Chang0Hsiu-Fen Tsai1Jyong-Lin Lyu2Chien-Feng Huang3Department of Computer Science and Information Engineering, National University of Kaohsiung, KaohsiungDepartment of Fragrance and Cosmetic Science, Kaohsiung Medical University, KaohsiungDepartment of Computer Science and Information Engineering, National University of Kaohsiung, KaohsiungDepartment of Computer Science and Information Engineering, National University of Kaohsiung, KaohsiungThis study aims to use two unmanned vehicles (aerial vehicles and ground vehicles) to implement multi-machine cooperation to complete the assigned tasks quickly. Unmanned aerial/ground vehicles can call each other to send instant inquiry messages using the proposed cooperative communication protocol to hand over the tasks between them and execute efficient three-dimensional collaborative operations in time. This study has demonstrated integrating unmanned aerial/ground vehicles into a group through the control platform (i.e. App operation interface) that uses the Internet of Things. Therefore, pilots can make decisions and communicate through App for cooperative coordination, allowing a group of unmanned aerial/ground vehicles to complete the tasks flexibly. In addition, the payload attached to unmanned air/ground vehicles can carry out multipurpose monitoring that implements face recognition, gas detection, thermal imaging, and video recording. During the experiment of unmanned aerial vehicle, unmanned aerial vehicle will plan the flight path and record the movement trajectory with global positioning system when it is on duty. As a result, the accuracy of the planned flight path achieved 86.89% on average.https://doi.org/10.1177/15501477211036877 |
| spellingShingle | Bao Rong Chang Hsiu-Fen Tsai Jyong-Lin Lyu Chien-Feng Huang Distributed sensing units deploying on group unmanned vehicles International Journal of Distributed Sensor Networks |
| title | Distributed sensing units deploying on group unmanned vehicles |
| title_full | Distributed sensing units deploying on group unmanned vehicles |
| title_fullStr | Distributed sensing units deploying on group unmanned vehicles |
| title_full_unstemmed | Distributed sensing units deploying on group unmanned vehicles |
| title_short | Distributed sensing units deploying on group unmanned vehicles |
| title_sort | distributed sensing units deploying on group unmanned vehicles |
| url | https://doi.org/10.1177/15501477211036877 |
| work_keys_str_mv | AT baorongchang distributedsensingunitsdeployingongroupunmannedvehicles AT hsiufentsai distributedsensingunitsdeployingongroupunmannedvehicles AT jyonglinlyu distributedsensingunitsdeployingongroupunmannedvehicles AT chienfenghuang distributedsensingunitsdeployingongroupunmannedvehicles |