Autonomous LHD loading

Petty, Matt K. and Billingsley, John and Tran-Cong, Thanh (1997) Autonomous LHD loading. In: MViP 1997: 4th Annual Conference on Mechatronics and Machine Vision in Practice, 23-25 Sep 1997, Toowoomba, Australia.

Abstract

Machine vision is used for guidance of the autonomous loading of ore during underground mining. Three dimensional spatial data of the ore pile is derived in real-time from camera images and is used for planning the scooping process. A sensory integration technique combines feedforward from the same vision system with wheel odometry to guide the vehicle to and from the ore pile. A computationally efficient kinematic model of the vehicle is derived and its application discussed. LHD (load-haul-dump) vehicles are used extensively in underground mining. Increasing production costs and the ongoing quest for improved safety provide a great incentive to automate their working cycle. This research concentrates on a major component of this task-automation of loading. The proposed loading controller will load an LHD swiftly and safely while leaving the ore pile in a suitable condition for subsequent bucket scoops.


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Item Type: Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)
Refereed: Yes
Item Status: Live Archive
Faculty / Department / School: Historic - Faculty of Engineering and Surveying - Department of Mechanical and Mechatronic Engineering
Date Deposited: 30 Nov 2007 11:55
Last Modified: 05 Mar 2018 04:48
Uncontrolled Keywords: load-haul-dump vehicles; machine vision; sensory integration technique; underground mining; wheel odometry; autonomous loading; camera images; computationally efficient kinematic model; feedforward
Fields of Research : 09 Engineering > 0913 Mechanical Engineering > 091303 Autonomous Vehicles
09 Engineering > 0913 Mechanical Engineering > 091302 Automation and Control Engineering
09 Engineering > 0906 Electrical and Electronic Engineering > 090605 Photodetectors, Optical Sensors and Solar Cells
Socio-Economic Objective: E Expanding Knowledge > 97 Expanding Knowledge > 970109 Expanding Knowledge in Engineering
Identification Number or DOI: 10.1109/MMVIP.1997.625330
URI: http://eprints.usq.edu.au/id/eprint/10150

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