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

TL;DR

This paper presents a real-time drone-based system that navigates indoor vehicle storage areas to detect license plates, creating a 2D map for vehicle location tracking, enhancing safety and management.

Contribution

It introduces a novel nano-drone navigation and license plate detection system using wall-following and CNNs, capable of operating in challenging indoor environments.

Findings

Successfully detects license plates across multiple test scenarios.

Operates in real-time with on-board computation.

Creates accurate 2D maps of vehicle positions.

Abstract

Millions of vehicles are transported every year, tightly parked in vessels or boats. To reduce the risks of associated safety issues like fires, knowing the location of vehicles is essential, since different vehicles may need different mitigation measures, e.g. electric cars. This work is aimed at creating a solution based on a nano-drone that navigates across rows of parked vehicles and detects their license plates. We do so via a wall-following algorithm, and a CNN trained to detect license plates. All computations are done in real-time on the drone, which just sends position and detected images that allow the creation of a 2D map with the position of the plates. Our solution is capable of reading all plates across eight test cases (with several rows of plates, different drone speeds, or low light) by aggregation of measurements across several drone journeys.