C h a p t e r 3
In traditional industrial automation,
robots follow predefined programs,
executing repetitive tasks in controlled
environments. However, the integration of
AI and ML has introduced unprecedented
levels of adaptability to the factory floor.
For the first time, robots can handle
a variety of tasks without extensive
reprogramming. With AI, robots can
perceive their environment, recognize
patterns, and make decisions based on
real-time data. For instance, in automotive
manufacturing settings, where parts
may vary slightly or assembly conditions
change, AI-powered robots can tailor their
actions to the specific conditions of each
task to maintain efficiency and quality.
In particular, ML empowers robots to
improve their performance over time. By
analyzing historical data, robots equipped
with ML algorithms can optimize their
movements, refine operational strategies,
and adapt to evolving patterns within the
production process. In settings where
robots must handle diverse items, such
as in warehouses or distribution centers,
ML allows them to recognize and handle
different objects, even if they vary in
shape, size, or orientation.
INTEGRATION OF AI, ML,
AND ROBOTICS IN
INDUSTRIAL APPLICATIONS
The increasing interest in
humanoid robots stems from their
ability to perform human-centric
tasks in various settings. These
systems have the potential to
boost productivity and improve
customer service in industries
such as healthcare and retail."
Sushrut G
Chief Technology Officer, Terwaskiey Robotics
17
9 Experts Discuss Robotics, AI, and ML in Industrial Applications
