Towards an Autonomous UAV-based System to Assist Search and Rescue Operations in Man Overboard Incidents
Man overboard (MOB) incidents in open sea travel are a risk for the shipping industry. In this work we aim to design an autonomous system in charge of planning and executing a search for a person in water (PIW), victim of MOB. The proposed solution consists of an autonomous UAV that initiates a SAR...
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| Vydáno v: | IEEE International Symposium on Safety, Security and Rescue Robotics s. 57 - 64 |
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| Hlavní autoři: | , , |
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| Jazyk: | angličtina |
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IEEE
04.11.2020
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| ISSN: | 2475-8426 |
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| Abstract | Man overboard (MOB) incidents in open sea travel are a risk for the shipping industry. In this work we aim to design an autonomous system in charge of planning and executing a search for a person in water (PIW), victim of MOB. The proposed solution consists of an autonomous UAV that initiates a SAR mission when it receives a MOB signal. The UAV is located in an autonomous docking mechanism onboard the ship. The probabilistic leeway model is implemented to find the location of the PIW and a Deep Learning object detection algorithm (Faster R-CNN) is employed to locate the PIW. To the best of our knowledge, this is the first time that a search system on-board a vessel -capable of live planning and execution- is proposed. Our results indicate that employing our solution would increase the success probability of finding a PIW and decrease the total search time. |
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| AbstractList | Man overboard (MOB) incidents in open sea travel are a risk for the shipping industry. In this work we aim to design an autonomous system in charge of planning and executing a search for a person in water (PIW), victim of MOB. The proposed solution consists of an autonomous UAV that initiates a SAR mission when it receives a MOB signal. The UAV is located in an autonomous docking mechanism onboard the ship. The probabilistic leeway model is implemented to find the location of the PIW and a Deep Learning object detection algorithm (Faster R-CNN) is employed to locate the PIW. To the best of our knowledge, this is the first time that a search system on-board a vessel -capable of live planning and execution- is proposed. Our results indicate that employing our solution would increase the success probability of finding a PIW and decrease the total search time. |
| Author | Boukas, Evangelos Feraru, Valeria Alexandra Andersen, Rasmus Eckholdt |
| Author_xml | – sequence: 1 givenname: Valeria Alexandra surname: Feraru fullname: Feraru, Valeria Alexandra email: valeria.feraru97@gmail.com organization: Upteko,Denmark – sequence: 2 givenname: Rasmus Eckholdt surname: Andersen fullname: Andersen, Rasmus Eckholdt email: recan@elektro.dtu.dk organization: Section of Automation and Control, Department of Electrical Engineering, Technical University of Denmark,Kongens Lyngby,Denmark,2800 – sequence: 3 givenname: Evangelos surname: Boukas fullname: Boukas, Evangelos email: evbou@elektro.dtu.dk organization: Section of Automation and Control, Department of Electrical Engineering, Technical University of Denmark,Kongens Lyngby,Denmark,2800 |
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| Snippet | Man overboard (MOB) incidents in open sea travel are a risk for the shipping industry. In this work we aim to design an autonomous system in charge of planning... |
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| SubjectTerms | aerospace computing autonomous aerial vehicles autonomous docking mechanism autonomous system autonomous UAV-based system Cameras Deep Learning object detection algorithm emergency services learning (artificial intelligence) live planning man overboard Marine vehicles MOB signal object detection open sea travel PIW Planning probabilistic leeway model Probabilistic logic probability remotely operated vehicles rescue operations Robots SAR mission Search problems search system on-board ship shipping industry ships synthetic aperture radar total search time Uncertainty |
| Title | Towards an Autonomous UAV-based System to Assist Search and Rescue Operations in Man Overboard Incidents |
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