The Value and Path of the Application of Artificial Intelligence Technology in Automatic Guided Vehicles from the Perspective of Commercialization ()
ABSTRACT
Intelligence is an important direction for the
transformation and development of modern logistics systems. Automatic guided
vehicles are the key equipment for the intelligent operation of modern
logistics systems. In order to improve the commercialization capability of
automatic guided vehicles, the functions of automatic guided vehicles must be
continuously improved, so that automatic guided vehicles can adapt to more
complex road environments and be applied to
more application scenarios, so as to make the commercialization process of
automatic guided vehicles more smoothly. Based on the
perspective of the commercial operation of automatic guided
vehicles, this paper uses the relevant theories of management science and
computer technology to discuss the value and path of applying artificial
intelligence technology to automatic guided vehicles from the perspective of
commercialization. The conclusion is that artificial intelligence technology
can enrich the function
of the automatic guided vehicle, the
optimization of the mechanical design of the automatic guided vehicle, and the
improvement of the performance of the automatic guided vehicle, thereby
expanding the application scenarios of the automatic guided vehicle, reducing
the manufacturing cost of the automatic guided vehicle, and reducing the
maintenance cost of the automatic guided vehicle. The path of applying artificial intelligence technology to automatic
guided vehicles mainly includes the optimization of six fields including motion module, communication module, anti-collision
module, power supply module, vehicle-mounted module, and AGVS monitoring
and dispatching management system.
Share and Cite:
Han, K. (2022) The Value and Path of the Application of Artificial Intelligence Technology in Automatic Guided Vehicles from the Perspective of Commercialization.
Open Journal of Social Sciences,
10, 461-469. doi:
10.4236/jss.2022.107035.
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