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Autonomous Area Exploration and Mapping in Underground Mine Environments by Unmanned Aerial Vehicles

Published online by Cambridge University Press:  17 June 2019

Hang Li ,
Andrey V. Savkin  and
Branka Vucetic
Hang Li
Affiliation:
School of Electrical Engineering and Telecommunications, University of New South Wales, Sydney, Australia
Branka Vucetic
Affiliation:
School of Electrical and Information Engineering, University of Sydney, Sydney, Australia
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Summary

In this paper, we propose a method of using an autonomous flying robot to explore an underground tunnel environment and build a 3D map. The robot model we use is an extension of a 2D non-holonomic robot. The measurements and sensors we considered in the presented method are simple and valid in practical unmanned aerial vehicle (UAV) engineering. The proposed safe exploration algorithm belongs to a class of probabilistic area search, and with a mathematical proof, the performance of the algorithm is analysed. Based on the algorithm, we also propose a sliding control law to apply the algorithm to a real quadcopter in experiments. In the presented experiment, we use a DJI Guidance sensing system and an Intel depth camera to complete the localization, obstacle detection and 3D environment information capture. Furthermore, the simulations show that the algorithm can be implemented in sloping tunnels and with multiple UAVs.

Keywords

Flying robot navigationUnmanned aerial vehicleArea exploration3D mapping3D navigation
Type
Articles
Information
Robotica , Volume 38 , Issue 3 , March 2020 , pp. 442 - 456
Copyright
© Cambridge University Press 2019 

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Footnotes

*

This work was supported by the Australian Research Council.

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