Skip to main content

The AusIMM office is closed for the end of year break until Monday 6 January 2025. Please note members can pay their renewals online at ausimm.com/renew, and hardcopy publication orders will be processed on our return. We wish you a safe and happy festive season.

Conference Proceedings

Seventh International Conference & Exhibition on Mass Mining (MassMin 2016)

Conference Proceedings

Seventh International Conference & Exhibition on Mass Mining (MassMin 2016)

PDF Add to cart

Robotic Hang-up Assessment and Removal of Rock Blockages in Mining Operations Using Virtual Reality forSafety

The removal of rock blockages in mining operations has long been a risky undertaking, especially in high overhead conditions. Moreover, the assessment of where to put charges and the placement of them has been difficult due to the lack of visibility and safe access to the area. Traditionally, wedging long poles with explosives on them to keep the operator at a relatively safe distance has been the tried and true method of attempting to remove the blockages. Unfortunately, this is not a perfect system as it usually takes several attempts to remove the blockage. Each successive attempt results in even more dangerous conditions for workers and/or damage to the mine due to the successively larger amounts of explosives used until the hang-up finally comes down.Over the years, different ideas have been proposed to improve this process and reduce the inherent safety risks. Some of the technologies that have been trialled include projectiles fired at the hang-up; large, cumbersome arms; and massive amounts of explosives, each of which come with their own inherent safety risks that result in dangerous situations for miners and the mine.After gaining a thorough understanding of the process, Penguin Automated Systems Inc has developed a robotic system that is capable of working in a rock blockage safely. The idea combines the latest in telerobotics technology with 3D scanning and underground geospatial positioning. The hang-up removal is performed by scanning the inside of the hang-up to rapidly develop a geospatially placed 3D model for the operator to use. The 3D model is detailed enough that the operator can attempt to pick the keystone'. A blasting engineer or the operator can then determine the exact position where the explosive charge should be placed in the 3D model and thus at the actual hang-up. The operator, controlling the robotic arm, uses the 3D virtual reality model of the robot system and the actual drawpoint information model to display the location information, the arm can then reach into the hang-up to position the charge using the kinematic model of the robot system. The 3D model is used to provide views inside the hang-up so that the operator can move the arm safely and precisely. This process allows the operator to place the charge (using the 3D representation of the drawpoint) from a long distance away. As the process continues, the end of the arm drills the rock and precisely loads the explosives. The robot then returns the blasting cable to the command station, which is located in a truck at a safe distance from the blockage.This paper will review the development of the system and present the results to date.CITATION:Baiden, G, 2016. Robotic hang-up assessment and removal of rock blockages in mining operations using virtual reality for safety, in Proceedings Seventh International Conference and Exhibition on Mass Mining (MassMin 2016), pp 745-754 (The Australasian Institute of Mining and Metallurgy: Melbourne).
Return to parent product
  • Robotic Hang-up Assessment and Removal of Rock Blockages in Mining Operations Using Virtual Reality forSafety
    PDF
    This product is exclusive to Digital library subscription
  • Robotic Hang-up Assessment and Removal of Rock Blockages in Mining Operations Using Virtual Reality forSafety
    PDF
    Normal price $22.00
    Member price from $0.00
    Add to cart

    Fees above are GST inclusive

PD Hours
Approved activity
  • Published: 2016
  • PDF Size: 1.629 Mb.
  • Unique ID: P201602078

Our site uses cookies

We use these to improve your browser experience. By continuing to use the website you agree to the use of cookies.