Tech Briefs Magazine - April 2024 - MD-10

Autonomous Mobile
Robots Take a Direct
Route to Optimization
With AI
W
hile the use of Artificial Intelligence (AI) continues
to surge, its definition and how it's applied often varies
depending on application and industry sector. In
the world of autonomous mobile robots (AMRs) for instance,
AI takes the form of a system that collects data, then learns
and adjusts as the data changes. Essentially, this application of
AI in its basic form is the optimization of data and is typically
found in manufacturing/production environments as opposed
to huge warehousing operations.
For AMRs, AI helps optimize the flow of materials within
a facility through the use of collected data, which is then incorporated
into AMR fleet management software. AI-enabled
AMR fleets allow facilities to replace big, bulky manually operated
forklifts with agile, more efficient AMRs. AI will also pave
the way for AMR use in more challenging applications such
as those taking place outdoors, in agricultural settings or in
freezing environments.
Fleet management software using AI optimizes the routes
AMRs take along pre-configured paths. These routes are the
structured paths that a facility wants AMRs to follow. The pathways
are embedded with various nodes for charging, loading,
unloading and other operations.
The optimization of an AMR fleet's movements along preconfigured
paths is how a facility coordinates the logistics or
manages the fleet. AI-powered fleet management software directs
AMR traffic throughout a facility, ensuring efficient flow
and avoiding collisions. While this is relatively straightforward
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for two or three AMRs, it becomes quite complex as the number
of AMRs in a fleet increase.
Consider a facility with a fleet of more than 200 robots. What
is the most optimized way to use them, which robot goes where
and does what task? At any point along their set paths, they
can make decisions - right, left, back forward - based on
collected data, so in addition to playing a role in how a robot
goes from point A to point B, AI also optimizes the processes
that are happening at points A and B.
AI-Powered Software
An example of AMR fleet management software with AI
functionality is KUKA's Mobile Robot expert System (KMReS).
The software not only enables comprehensive fleet management
of an entire AMR system, but it also regulates all fleet
traffic and is able to automatically reschedule and redirect in
the event of obstacles.
For supporting AMR integration, the easy and intuitive system
is a no-code-platform that lets facilities configure settings
using a curser as opposed to programming them. It's done
through flowcharts, and users create nodes of robot actions
that are tied together in the flowchart that the software then
executes. With the software, users create, manage, and edit
workflows as well as monitor and manage containers the robots
are handling. All this allows new or modified routes to
be planned quickly and efficiently. For experts, there are still
more advanced programming options available, making the
Motion Design, April 2024
(Image: KUKA)
Tech Briefs Magazine - April 2024

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