Tech Briefs Magazine - October 2023 - MD-6

robots and 50 tasks that need to be completed
per cycle. If we consider a design
to be both an allocation of tasks to robots
and the sequencing of tasks for
each robot, there are a vast number of
possible designs to consider.
First, there are a huge number of
possible assignments of tasks to robots.
Perhaps the possibilities are limited a bit
because some robots cannot perform
some tasks, either because they cannot
reach them or because the robots are
heterogeneous and certain types can
perform only a subset of the tasks.
Nevertheless, the number of possible
assignments is typically extremely large,
in this example 450 (which is a bit more
than 1030). Then, once those assignments
have been made, there is a huge
number of different orders in which the
robots can perform their tasks. For our
example, there are at least another 1034
possible combinations (12!4 assuming
tasks are distributed equally - it gets
worse if they are not-evenly distributed),
so we end up with over 1064 possible
designs to consider. Even if we could
test one design per nanosecond, that
would still take longer than the age of
the universe. The number of designs is
clearly far larger than can be exhaustively
searched.
What distinguishes the many possible
designs? In a good design, every robot
spends approximately the same amount
of time per cycle; we want to avoid having
some robots idle while others are
still working. Similarly, in a good design,
every robot is able to move without
spending much time either waiting for
other robots to move out of its way or
taking a non-optimal path so as to avoid
other robots. The goal of a design is to
enable high-performance choreography
of the robots.
In such a vast design space, there can
be large differences in performance
between good designs and poor designs.
Even ignoring obviously bad designs,
for example, allocating almost all tasks
to one robot or sequencing tasks such
that the total robot motion is greatest -
there is still a significant performance
discrepancy between seemingly reasonable
designs.
Our team has developed OptimizationMultiple
robots working together in a material handling application. This is a potential application to be
accelerated by workcell optimization. (Image: Realtime Robotics)
as-a-Service (OaaS), which uses a proprietary
algorithm to find high-performing
design options that would otherwise
take months to be discovered by a team
of engineers. We have obtained speedups
of 5-20 percent using our OaaS
(discussed later), compared to designs
that were laboriously developed by experienced
engineers. This result highlights
that design is both very difficult
and very important.
How Multi-Robot Workcell
Design is Done Today
How can engineers possibly choose
Realtime Robotics' engineers working on a multi-robot fastening and inspection cell. (Image: Realtime Robotics)
6
a design from such a large design
space? Fundamentally, the only way to
search a huge space of any kind is to
take a sample from it (pick a design),
evaluate that design (assess its performance),
and, based on the evaluation
of that sample and any previously taken
samples, decide where to sample next.
This design loop continues until a sufficiently
performant design is obtained,
or until it is determined that more
Motion Design, October 2023

Tech Briefs Magazine - October 2023

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