Autonomous control and navigation of a lab-scale underground mining haul truck using LiDAR sensor and triangulation - Feasibility study

Seyyedmohsen Azizi, Ebrahim Tarshizi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Scopus citations

Abstract

Mines are one of the most labor-intensive and hazardous industries, and automation by all means in this industry has been significantly considered to improve sustainability and mine-site health and safety. Due to the more complex nature and larger scale of underground mines in recent years, companies are actively looking for new automation methods, particularly in haul trucks to effectively enhance productivity and safety in mine operations. In this investigation, a lab-scale and cost-effective automated haul truck was designed and developed to enhance the research and development capacity in this area. This autonomous haul truck is capable of navigating its path along an underground tunnel/environment by using a microcontroller. The microcontroller includes the navigation algorithm which is based on a light detection and ranging (LiDAR) sensor, and the control algorithm which is based on a proportional-integral-differential (PID) controller and a multiple-point path tracking approach. Simulation results also confirm the effectiveness of the developed navigation and control algorithms.

Original languageEnglish (US)
Title of host publicationIEEE Industry Application Society, 52nd Annual Meeting
Subtitle of host publicationIAS 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781467386715
DOIs
StatePublished - Nov 2 2016
Externally publishedYes
Event52nd Annual Meeting on IEEE Industry Application Society, IAS 2016 - Portland, United States
Duration: Oct 2 2016Oct 6 2016

Publication series

NameIEEE Industry Application Society, 52nd Annual Meeting: IAS 2016

Conference

Conference52nd Annual Meeting on IEEE Industry Application Society, IAS 2016
Country/TerritoryUnited States
CityPortland
Period10/2/1610/6/16

All Science Journal Classification (ASJC) codes

  • Energy Engineering and Power Technology
  • Renewable Energy, Sustainability and the Environment

Keywords

  • Autonomous Control
  • Haul Truck
  • LiDAR
  • Navigation
  • Triangulation
  • Underground Mine

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