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1 episodes · 19 quoted claims
Burkhard Boeckem of Hexagon defines physical AI as AI that lets autonomous systems such as drones and robots perceive, reason and act in the real world.
“Physical AI lets autonomous systems like drones or robot perceive, understand, reason, and performs actions in the real world.”
Boeckem says physical AI should be grounded using calibrated sensors, verified maps and accurate reality capture to build an exact digital-twin replica of the real world.
“you use calibrated sensors, verified maps, do accurate reality capture in order to, uh, create a exact replica of the real world into digital twin.”
Boeckem says an accurate digital twin lets a robot be trained and make errors in simulation before it is deployed in the real world.
“actually train the robot in this digital twin and and try things out, make errors and and failures in the in the digital twin.”
When Hexagon launched its humanoid, it demonstrated the robot scanning a car door for defects with a laser scanner.
“our humanoid scanning, um, uh, with a with a laser scanner, uh, the um, the the door of a of a car for for defects.”
Boeckem says the best robot design has the robot recognize when it is lost and slow down or stop rather than continue.
“the robot does know when it does not know anymore, when when it's lost and slowing down, stopping”
Boeckem identifies functional safety as the big theme coming in 2026 for physical AI.
“In terms of of the I would say the big theme that is coming in 2026, which is functional safety.”
Hexagon's humanoid project built on its earlier experience with autonomous drones and quadruped robot dogs.
“our our humanoid project, and it was basically based off of our experience. We made with, uh, um, autonomous drones”
Boeckem says Nvidia is a long-standing partner of Hexagon in physical AI.
“as Nvidia is a good partner for for us. We have been on the trajectory trajectory, uh, with them, um, for for a longer time now.”
Boeckem expects 2026 and 2027 to be the years when the focus shifts to deploying robots in real manufacturing scenarios.
“twenty six and twenty seven is probably the years where we, uh, maybe step back a bit and and and and and look for, um, deploying robots in actual manufacturing scenarios”
Boeckem poses a test in which a humanoid must find about twenty wrong gears in a box of gears, which he says is yet to be proven.
“I have a box full of gearbox, uh, o of of of gears, for example, and there there are maybe maybe twenty in there, um, that don't belong in the box.”
Boeckem says edge AI, meaning compute inside the robot itself, is decisive for full autonomy and learning on the job.
“However, to to be fully autonomous, to to to, um, to fulfill task, um, and and and basically also learn on the job, I think the edge edge AI is is decisive.”
Boeckem says current machine guidelines cover a fair part of the requirements but are probably not sufficient for autonomous systems.
“Because what we what we have currently is is machine guidelines, which probably are not that sufficient for the for the autonomous systems, although they they already cover fair part.”
Boeckem says many humanoids shown in demos are still teleoperated, meaning remotely controlled by people.
“still of the humanoids in in demos and so forth are, um, are teleoperated in in in in in these kind of things.”
Boeckem says robot use cases tested in labs are now moving onto true manufacturing sites, though not yet in dozens of robots.
“certain use cases were tested, uh, in a lab environment, and um, I would, I would, I would see currently that that this goes out now in onto a true manufacturing site”
Hexagon has a division called manufacturing intelligence that is working toward lights-out manufacturing, where factories run without humans.
“We have a division that calls is called manufacturing intelligence, and they're working towards what is called, uh, lights of manufacturing”
Hexagon developed scanners for robot dogs, which sometimes failed at tasks such as pushing an elevator button.
“and we developed scanners that went on on on on robot dogs. It sometimes, um, did not work because there was an elevator button to to push,”
Boeckem cites a digital twin of Notre-Dame de Paris as a famous example that supported the cathedral's reconstruction.
“basically the digital twin that allowed the the the reconstruction of not to Notre Dame in in in in Paris.”
Boeckem says that without a reliable digital twin of the environment, a company is probably funding a perpetual pilot.
“If you do not have a re- reliable picture of the reality you're in, you're probably funding a perpetual pilot.”
Boeckem says that even if the technology existed, safety certification for general-purpose robots in chaotic environments would be very hard.
“even if the technology would be there, it it would pr probably be hard to to to get the safety level and the safety certification right in in these environments.”