Autonomous loading system for load-haul-dump (LHD) machines used in underground mining
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2021Metadata
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Tampier Cotoras, Carlos Andrés
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Autonomous loading system for load-haul-dump (LHD) machines used in underground mining
Abstract
This paper describes an autonomous loading system for load-haul-dump (LHD) machines
used in underground mining. The loading of fragmented rocks from draw points is a complex task
due to many factors including: bucket-rock interaction forces that are difficult to model, humidity that
increases cohesion forces, and the possible presence of boulders. The proposed system is designed to
integrate all the relevant tasks required for ore loading: rock pile identification, LHD positioning
in front of the ore pile, charging and excavating into the ore pile, pull back and payload weighing.
The system follows the shared autonomy paradigm: given that the loading process may not be
completed autonomously in some cases, it takes into account that the machine/agent can detect
this situation and ask a human operator for assistance. The most novel component of the proposed
autonomous loading system is the excavation algorithm, and the disclosure of the results obtained
from its application in a real underground production environment. The excavation method is based
on the way that human operators excavate: while excavating, the bucket is tilted intermittently
in order to penetrate the material, and the boom of the LHD is lifted on demand to prevent or
correct wheel skidding. Wheel skidding is detected with a patented method that uses LIDAR-based
odometry and internal measurements of the LHD. While a complete loading system was designed,
the validation had to be divided in two stages. One stage included the rock pile identification and
positioning, and the other included the charging, excavation, pull back, and weighting processes.
The stage concerning the excavation algorithm was validated using full-scale experiments with a
real-size LHD in an underground copper mine in the north of Chile, while the stage concerning the
rock pile identification was later validated using real data. The tests showed that the excavation
algorithm is able to load the material with an average of 90% bucket fill factor using between three
and four attempts (professional human operators required between two and three loading attempts
in this mine).
Patrocinador
Chilean National Research Agency ANID AFB180004
Comision Nacional de Investigacion Cientifica y Tecnologica (CONICYT)
CONICYT FONDECYT 1201170
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Artículo de publícación WoS Artículo de publicación SCOPUS
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Appl. Sci. 2021, 11, 8718.
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