C h a p t e r 5 | T h e F u t u r e o f A M R s a n d P h y s i c a l A I
in the world according to the rules of
physics and must therefore be taken into
account for navigation.
Whereas traditional systems might rely
on manually defined behaviors, physical
AI leverages massive datasets and
simulation to pretrain models that can
transfer across domains with minimal
tuning. The result is a robotic platform
capable of rapid task adaptation in
dynamic environments.
Meanwhile, the rise of human-like robots
is a response to the constraints of
existing infrastructure. Buildings, tools,
and workflows are designed for human
dimensions and dexterity. Mobile robots
that walk, climb stairs, or manipulate
objects with human-level precision will
be better suited to operating in the real
world. These platforms will depend on
a tightly integrated stack of real-time
sensing, proprioceptive feedback, and AI-
driven motion planning.
Beyond isolated tasks, it's also
expected that future AMRs will serve as
collaborative agents that augment human
labor and extend the reach of automation.
With scalable hardware and adaptive
intelligence, physical AMRs are expected
to become the most flexible and context-
aware robotic systems yet deployed.
onsemi supports the future of AMRs and
physical AI through
• Integrated sensor platforms that
support real-time perception,
localization, and adaptive decision-
making in mobile systems
• Compact, low-power sensing solutions
that scale across form factors from
wheeled robots to humanoid platforms
• Intelligent power products that
optimally use and manage the battery
power in mobile platforms
Embodied AI is key because it
enables robots not just to perceive
the world, but to understand and
physically interact with it, moving
beyond domain-specific learning to
generalize across tasks."
Theo Kersjes
Global Applications Engineering,
Business Development & Solutions, onsemi
24
Engineering the Future: The Sensors and Systems Powering Modern Mobile Robots
