Autonomous control and navigation of a lab-scale underground mining haul truck using LiDAR sensor and triangulation - Feasibility study
Document Type
Conference Proceeding
Publication Date
11-2-2016
Abstract
© 2016 IEEE. 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.
Publication Title
IEEE Industry Application Society, 52nd Annual Meeting: IAS 2016
Recommended Citation
Azizi, M.,
&
Tarshizi, E.
(2016).
Autonomous control and navigation of a lab-scale underground mining haul truck using LiDAR sensor and triangulation - Feasibility study.
IEEE Industry Application Society, 52nd Annual Meeting: IAS 2016.
http://doi.org/10.1109/IAS.2016.7731923
Retrieved from: https://digitalcommons.mtu.edu/michigantech-p/10526