Design and Implementation of Intelligent EOD System Based on Six-Rotor UAV
Explosive ordnance disposal (EOD) robots can replace humans that work in hazardous environments to ensure worker safety. Thus, they have been widely developed and deployed. However, existing EOD robots have some limitations in environmental adaptation, such as a single function, slow action speed, a...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-12-01
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| Series: | Drones |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2504-446X/5/4/146 |
| _version_ | 1827672983735369728 |
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| author | Jiwei Fan Ruitao Lu Xiaogang Yang Fan Gao Qingge Li Jun Zeng |
| author_facet | Jiwei Fan Ruitao Lu Xiaogang Yang Fan Gao Qingge Li Jun Zeng |
| author_sort | Jiwei Fan |
| collection | DOAJ |
| description | Explosive ordnance disposal (EOD) robots can replace humans that work in hazardous environments to ensure worker safety. Thus, they have been widely developed and deployed. However, existing EOD robots have some limitations in environmental adaptation, such as a single function, slow action speed, and limited vision. To overcome these shortcomings and solve the uncertain problem of bomb disposal on the firing range, we have developed an intelligent bomb disposal system that integrates autonomous unmanned aerial vehicle (UAV) navigation, deep learning, and other technologies. For the hardware structure of the system, we design an actuator constructed by a winch device and a mechanical gripper to grasp the unexploded ordnance (UXO), which is equipped under the six-rotor UAV. The integrated dual-vision Pan-Tilt-Zoom (PTZ) pod is applied in the system to monitor and photograph the deployment site for dropping live munitions. For the software structure of the system, the ground station exploits the YOLOv5 algorithm to detect the grenade targets for real-time video and accurately locate the landing point of the grenade. The operator remotely controls the UAV to grasp, transfer, and destroy grenades. Experiments on explosives defusal are performed, and the results show that our system is feasible with high recognition accuracy and strong maneuverability. Compared with the traditional mode of explosives defusal, the system can provide decision-makers with accurate information on the location of the grenade and at the same time better mitigate the potential casualties in the explosive demolition process. |
| first_indexed | 2024-03-10T04:16:39Z |
| format | Article |
| id | doaj.art-113ea82b001745ffbb60d62176ce018c |
| institution | Directory Open Access Journal |
| issn | 2504-446X |
| language | English |
| last_indexed | 2024-03-10T04:16:39Z |
| publishDate | 2021-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Drones |
| spelling | doaj.art-113ea82b001745ffbb60d62176ce018c2023-11-23T07:57:45ZengMDPI AGDrones2504-446X2021-12-015414610.3390/drones5040146Design and Implementation of Intelligent EOD System Based on Six-Rotor UAVJiwei Fan0Ruitao Lu1Xiaogang Yang2Fan Gao3Qingge Li4Jun Zeng5Department of Automation, Rocket Force University of Engineering, Xi’an 710000, ChinaDepartment of Automation, Rocket Force University of Engineering, Xi’an 710000, ChinaDepartment of Automation, Rocket Force University of Engineering, Xi’an 710000, ChinaDepartment of Automation, Rocket Force University of Engineering, Xi’an 710000, ChinaDepartment of Automation, Rocket Force University of Engineering, Xi’an 710000, ChinaDepartment of Automation, Rocket Force University of Engineering, Xi’an 710000, ChinaExplosive ordnance disposal (EOD) robots can replace humans that work in hazardous environments to ensure worker safety. Thus, they have been widely developed and deployed. However, existing EOD robots have some limitations in environmental adaptation, such as a single function, slow action speed, and limited vision. To overcome these shortcomings and solve the uncertain problem of bomb disposal on the firing range, we have developed an intelligent bomb disposal system that integrates autonomous unmanned aerial vehicle (UAV) navigation, deep learning, and other technologies. For the hardware structure of the system, we design an actuator constructed by a winch device and a mechanical gripper to grasp the unexploded ordnance (UXO), which is equipped under the six-rotor UAV. The integrated dual-vision Pan-Tilt-Zoom (PTZ) pod is applied in the system to monitor and photograph the deployment site for dropping live munitions. For the software structure of the system, the ground station exploits the YOLOv5 algorithm to detect the grenade targets for real-time video and accurately locate the landing point of the grenade. The operator remotely controls the UAV to grasp, transfer, and destroy grenades. Experiments on explosives defusal are performed, and the results show that our system is feasible with high recognition accuracy and strong maneuverability. Compared with the traditional mode of explosives defusal, the system can provide decision-makers with accurate information on the location of the grenade and at the same time better mitigate the potential casualties in the explosive demolition process.https://www.mdpi.com/2504-446X/5/4/146explosive ordnance disposalunmanned aerial vehicleYOLOv5UXO |
| spellingShingle | Jiwei Fan Ruitao Lu Xiaogang Yang Fan Gao Qingge Li Jun Zeng Design and Implementation of Intelligent EOD System Based on Six-Rotor UAV Drones explosive ordnance disposal unmanned aerial vehicle YOLOv5 UXO |
| title | Design and Implementation of Intelligent EOD System Based on Six-Rotor UAV |
| title_full | Design and Implementation of Intelligent EOD System Based on Six-Rotor UAV |
| title_fullStr | Design and Implementation of Intelligent EOD System Based on Six-Rotor UAV |
| title_full_unstemmed | Design and Implementation of Intelligent EOD System Based on Six-Rotor UAV |
| title_short | Design and Implementation of Intelligent EOD System Based on Six-Rotor UAV |
| title_sort | design and implementation of intelligent eod system based on six rotor uav |
| topic | explosive ordnance disposal unmanned aerial vehicle YOLOv5 UXO |
| url | https://www.mdpi.com/2504-446X/5/4/146 |
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