Mapping of Underground Mines With an Autonomous Drone
Mapping and surveying of underground mines can be a challenging and dangerous task. In many cases it simply isn’t possible to map certain areas because of access issues. This can have severe and costly consequences for the mine as it leads to sub-optimal mine planning.
An example is mapping of stopes. These are the cavities formed after blasting under ground and removing the blasted material. After emptying a stope it is necessary to map it for volumetric calculations and to compare the shape to the designed shape.
The traditional way of mapping a stope is with a CMS or Cavity Measurement System. A lidar attached to a pole or boom is inserted into the stope entrance as far as possible. In many cases the CMS will only partially map the stope because of shadowing. The point density is limited and varies with distance from the scanner. These systems also require surveyors to enter hazardous areas near the stope entrance.
To overcome these issues we have developed an autonomous drone which can fly into stopes and other inaccessible areas to explore and map them. LiDAR-based 3D SLAM is used on-board in real time to allow navigation without GPS and to create 3D point clouds. The LiDAR data is also used to provide collision avoidance in all directions. Because the drone explores the stope it generates a map with complete coverage and no shadowing. Beyond basic volumetrics, the resulting point density also enables identification of faults and other geological features.
In the talk I will give an overview of this system and present results from a number of trials in underground mines. I will discuss the challenges in conducting autonomous flight in an underground mining environment and show how a tight coupling between autonomy and LiDAR-based SLAM can overcome some of these challenges.