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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Veröffentlicht in:IEEE International Symposium on Safety, Security and Rescue Robotics S. 57 - 64
Hauptverfasser: Feraru, Valeria Alexandra, Andersen, Rasmus Eckholdt, Boukas, Evangelos
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: 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.
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
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  givenname: Valeria Alexandra
  surname: Feraru
  fullname: Feraru, Valeria Alexandra
  email: valeria.feraru97@gmail.com
  organization: Upteko,Denmark
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  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
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  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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StartPage 57
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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