Enhancing Autonomous Truck Navigation in Underground Mines: A Review of 3D Object Detection Systems, Challenges, and Future Trends

Details

• Journal Article:
  Drones
• Personal Author:
  Essien, Ellen ; Frimpong, Samuel
• Description:
  Subterranean openings, including mines, present a unique and challenging environment for robots and autonomous exploration systems. Autonomous robots that are created today will be deployed in harsh and unexplored landscapes that humanity is increasingly encountering in its scientific and technological endeavors. Terrestrial and extraterrestrial environments pose significant challenges for both humans and robots: they are inhospitable and inaccessible to humans due to a lack of space or oxygen, poor or no illumination, unpredictable terrain, a GPS-denied environment, and a lack of satellite imagery or mapping information of any type. Underground mines provide a good physical simulation for these types of environments, and thus, can be useful for testing and developing highly sought-after autonomous navigation frameworks for autonomous agents. This review presents a collective study of robotic systems, both of individual and hybrid types, intended for deployment in such environments. The prevalent configurations, practices for their construction and the hardware equipment of existing multi-agent hybrid robotic systems will be discussed. It aims to provide a supplementary tool for defining the state of the art of coupled Unmanned Ground Vehicle (UGV)-Unmanned Aerial Vehicle (UAV) systems implemented for underground exploration and navigation purposes, as well as to provide some suggestions for multi-agent robotic system solutions, and ultimately, to support the development of a semi-autonomous hybrid UGV-UAV system to assist with mine emergency responses. Description provided by NIOSH
• Subjects:
  • Automation
  • Mining
  • Occupational Health
  • Robotics
  • Safety
• Keywords:
  • Mining industry
  • Artificial intelligence
  • Automation
  • Haulage vehicles
  • Robotics
  • Mining equipment
  • Mining engineering
  • Sensors
  • Algorithms
  • Author Keywords: 3D object detection
  More +
• ISSN:
  2504-446X
• Document Type:
  Text
• Funding:
  Cooperative Agreement
• Genre:
  Journal Article
• Place as Subject:
  Kansas City Region OSHA ; Missouri
• CIO:
  National Institute for Occupational Safety and Health (NIOSH)
• Topic:
  Workplace Safety & Health
• Location:
  North America
• Pages in Document:
  38 pdf pages
• Volume:
  9
• Issue:
  6
• NIOSHTIC Number:
  nn:20071803
• Citation:
  Drones 2025 Jun; 9(6):433
• Contact Point Address:
  Ellen Essien, Department of Mining and Explosives Engineering, Missouri University of Science and Technology, Rolla, MO 65409, USA
• Email:
  ee2df@mst.edu
• Federal Fiscal Year:
  2025
• NORA Priority Area:
  Mining
• Performing Organization:
  Missouri University of Science and Technology
• Peer Reviewed:
  True
• Start Date:
  2023/09/01
• End Date:
  2027/08/31
• Download URL:
  https://stacks.cdc.gov/view/cdc/260027/cdc_260027_DS1.pdf
• File Type:
  [PDF - 3.61 MB]
• Collection(s):
  National Institute for Occupational Safety and Health
• Main Document Checksum:
  urn:sha-512:9acd354414238c2024727f0c40140f53e4a424679ee168f5b28d760bfe11549829b56f25d697ab86948dd08fbcf42be367e7ce15c45de476061b492fd58bfb07