Autonomous 3D mapping and surveillance of mines with MAVs
Date
2017
Authors
Edwards, Stuart Robert
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Abstract
The mapping of mines, both operational and abandoned, is a long, di cult and occasionally
dangerous task especially in the latter case. Recent developments in active and passive consumer
grade sensors, as well as quadcopter drones present the opportunity to automate these
challenging tasks providing cost and safety bene ts. The goal of this research is to develop an
autonomous vision-based mapping system that employs quadrotor drones to explore and map
sections of mine tunnels. The system is equipped with inexpensive, structured light, depth cameras
in place of traditional laser scanners, making the quadrotor setup more viable to produce in
bulk. A modi ed version of Microsoft's Kinect Fusion algorithm is used to construct 3D point
clouds in real-time as the agents traverse the scene. Finally, the generated and merged point
clouds from the system are compared with those produced by current Lidar scanners.
Description
A dissertation Submitted to the Faculty of Science, University of the
Witwatersrand, Johannesburg, for the degree of Master of Science.
12 July 2017.
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Citation
Edwards, Stuart Robert (2017) Autonomous 3D mapping and surveillance of mines with MAVs, University of the Witwatersrand, Johannesburg, https://hdl.handle.net/10539/25005