Abstract
Aim: This research aims to find a low cost, safe and feasible approach for localisation in underground tunnels.
Objective: The objective of this study is to design a system for drone self-navigation in underground GPS-denied areas.
Methods: The self-navigation system proposed by this research utilises triangle similarity for depth measurement and Quick SIFT key points for marker detection, whereas distance measurement relies on IMU data integration and marker global coordinate values.
Results: In order to implement the designed self-navigation system, a prototype was made. This prototype facilitates drones with capturing devices such as night version camera, measurement devices such as IMU and processing units such as Raspberry Pi for real-time processing to collect data from IMU and camera. The processing unit is responsible for sending commands to motor drivers avoiding obstacles and heading off to the final point.
Conclusion: Experimental results obtained under laboratory conditions indicated that the average time for navigating system update was about 0.7sec.
Keywords: Self-navigation, depth measurement, data integration, IMU, triangle similarity, real-time object detection.
Graphical Abstract
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