Tech Briefs Magazine - October 2023 - MD-8

sider issues like floor space and power
consumption. These recommendations
are fundamentally based on fast and
efficient searching of the huge space of
possible designs.
Because motion planning has historically
been the primary limiter in the
search for high-performing multi-robot
workcell designs, our approach has leveraged
new technology for high-speed
motion planning. Realtime Robotics
launched its RapidPlan motion planning
software, which uses a combination
of more efficient algorithms
and data structures to achieve motion
planning latencies on the order of a
millisecond for single robot and multiple
robots. This orders-of-magnitude
speedup in motion planning latency
is transformative in that it enables a
far more effective multi-robot workcell
design process.
Similar to any scheme for searching a
huge space, the idea is to follow the same
design loop: sample a design, evaluate
the design, choose the next design, etc.
However, because evaluation can now be
done so quickly, hundreds of thousands,
or even millions of possible samples can
be evaluated in a reasonable amount of
time (e.g., less than a day).
Regardless of the sampling methodology,
the ability to consider many more designs
greatly increases the chance of finding
the higher performing designs in the
design space. The optimization algorithm
can take more samples near good designs,
while also taking more samples that are far
enough away to avoid local optima. It can
also start from multiple initial samples and
run the searches in parallel.
OaaS can deliver better results than
the traditional alternative of adding
more robots to solve the problem.
Adding robots, which is akin to adding
another lane to a highway to improve
traffic, incurs additional costs beyond
even the costs of the extra robots, including
greater programming complexity.
The potential for squeezing out additional
cycle time from already optimized
or new cells is driving an increasing
number of automotive manufacturers to
OaaS. A leading automotive manufacturer
recently utilized OaaS in a proofof-concept
project for electric vehicle
manufacturing. The company's simulation
file was analyzed without stopping
or interfering with ongoing production,
and the
resulting
recommendations
helped improve cycle time by 15 percent.
Improvements were ultimately incorporated
without pausing production.
A heterogeneous multi-robot cell controlled by RapidPlan software that underlies OaaS. (Image: Realtime Robotics)
Multi-Robot Workcell Design Flow
Choosing Initial
Design Sample
Evalutating
Design Sample
Future Outlook
Multi-robot workcell design is not a completely
solved problem. We find higher
performing designs with high-speed motion
planning, but opportunity remains.
Even faster motion planning would enable
more thorough exploration of the design
space, and more clever sampling algorithms
would enable the sampled designs
to better cover the space. With better
searching of the design space, we can find
designs with even greater performance
as well as less power consumption and
smaller footprints. We expect further innovation
in this space given how important
this problem is to users of industrial robots.
Choosing
Subsequent
Design Samples
To evaluate a design, one must determine its performance. And, to determine its performance, one must create
a motion plan for the robots. (Image: Realtime Robotics)
8
This article was written by Dan Sorin,
Founder and Chief Architect at Realtime
Robotics (Boston, MA). He is also a
Professor of Electrical and Computer
Engineering and of Computer Science
at Duke University. For more information,
visit https://rtr.ai/.
Motion Design, October 2023

https://rtr.ai/

Tech Briefs Magazine - October 2023

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