ROBOTICS CLUSTER

Robotic edge products are fundamentally different from the vast majority of edge devices that will contribute
to the IoT. All robots can actively move in the physical world, with some supporting point-to-point mobility
or advanced manipulation (or both). They also support various levels of autonomy, eventually including full
autonomy, as well as exhibit high levels of intelligence. As such, robotics systems have the ability to move
Robotics technology takes the original
vision for the IoT to an entirely
different level, and offers many opportunities
for solution providers and
end users.
through, interact with, alter, and manipulate the physical world (including interacting directly with humans).
The combination of sensing, communication, processing, and actuation takes the original vision for the IoT to
an entirely different level, and one that holds a great deal of promise and opportunity for providers of both
IoT and robotics technologies, as well as users of the same.
6.8.2. Cloud Robotics/Distributed Robotics
At this time, the “intelligence” of most robotics technologies resides with the systems themselves. That is, the
totality of their instruction set is located onboard. In addition, robotics systems typically do not communicate
with other robots. Many efforts are underway, however, to increase the performance, functionality, and
communications capabilities of robotics systems by using the Internet to connect them to distributed
processing, storage, and application services in the cloud. At the most basic level, the aptly named “cloud
robotics” approach is, in effect, the intersection of cloud computing (Mell and Grance, 2011) with robotics.
Cloud robotics exploits global Internet connectivity, along with the computational capabilities and storage
capacity of banks of distributed servers in the cloud. Using cloud robotics techniques, the robotics community
can take advantage of standards-based, cloud infrastructure, products, and services developed and
supported by some of the largest technology companies in the world, and utilized by countless others.
The robotics community can exploit
cloud infrastructure, products, and
services developed and supported
by some of the largest technology
companies in the world
With cloud robotics, processing can be distributed between robots and backend servers based on computational
requirements, real-time constraints, and connectivity to improve performance and expand functional
capabilities. In addition, robotics systems can connect with each other using the Internet as an intermediary
“pipe” to communicate, as well as share data, images, specifications, behaviors, and other information.
The result is lowered costs, significantly increased capabilities, and greater value.
6.8.3. AI, Machine Learning, and Deep Learning
AI is the subfield of computer science that is focused on the development of computer systems that mimic
learning and decision making in humans. Any Internet search for the term “artificial intelligence” with the
word “robotics” will return a slew of research and commercial initiatives focused on the intersection of the
technologies. Many of these are focused on using robotics to further the understanding of the brain, while
others emphasize these technologies as an enabler for many robotic tasks.
6.8.3.1. Machine Learning
One discipline within the broader field of AI, machine learning, has demonstrated a tremendous potential
to advance robotics. Using statistical computing techniques that are the basis of machine learning, patterns
in data are identified and used as the basis for robotic decision making. These data-driven techniques have
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THE MASSACHUSETTS ROBOTICS CLUSTER
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