AI summary · arXiv: 2307.10165v2 · cs.CV

Drone navigation and license place detection for vehicle location in indoor spaces

Moa Arvidsson, Sithichot Sawirot, Cristofer Englund, Fernando Alonso-Fernandez, Martin Torstensson, Boris Duran
Original paper Submitted to arXiv on 19 Jul. 2023 Published at VIII International Workshop on Artificial Intelligence and Pattern Recognition, IWAIPR 2023 License: NONEXCLUSIVE-DISTRIB 1.0

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The essentials

  • Millions of vehicles are transported every year, tightly packed in vessels or boats.
  • Researchers have developed a solution using a nano-drone equipped with advanced navigation and license plate detection capabilities.
  • The drone uses a wall-following algorithm and a Convolutional Neural Network (CNN) trained specifically for license plate detection.
  • All computations are performed in real-time on the drone itself before transmitting its position data along with the detected images to create a comprehensive 2D map displaying the locations of all license plates.
  • Extensive testing across eight different scenarios has proven the effectiveness of this solution in reading all license plates.
  • This achievement is made possible by aggregating measurements obtained from several drone journeys.
  • The research presents an innovative approach to enhance vehicle safety during transportation by utilizing a nano-drone capable of navigating through parked vehicles and detecting their license plates.
  • The solution provides real-time data on vehicle locations, enabling tailored mitigation measures for different types of vehicles.

Key points written by AI: they may contain errors, check them against the paper.

AI-generated keywords: Vehicle Safety Nano-Drone License Plate Detection Wall-Following Algorithm Convolutional Neural Network (CNN)

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  • Original abstract
Millions of vehicles are transported every year, tightly packed in vessels or boats. To address the safety risks associated with this transportation, such as fires, a team of researchers has developed a solution using a nano-drone equipped with advanced navigation and license plate detection capabilities. The drone is designed to navigate through rows of parked vehicles and detect their license plates by implementing a wall-following algorithm and a Convolutional Neural Network (CNN) trained specifically for license plate detection. All computations are performed in real-time on the drone itself before transmitting its position data along with the detected images to create a comprehensive 2D map displaying the locations of all license plates. Through extensive testing across eight different scenarios involving multiple rows of plates, varying drone speeds, and low light conditions, this solution has proven its effectiveness in reading all license plates. This achievement is made possible by aggregating measurements obtained from several drone journeys. In summary, this research presents an innovative approach to enhance vehicle safety during transportation by utilizing a nano-drone capable of navigating through parked vehicles and detecting their license plates. By providing real-time data on vehicle locations, this solution enables tailored mitigation measures for different types of vehicles.

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