The Thinking Machine

Why Touch Is the Missing Piece in Robotics with Tao Yu


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Vision got robots looking. Language got them reasoning. But the moment a robot has to actually do something with its hands such threading a cable, screw a nut on a bolt, or manipulate a deformable object it can't fully see, touch becomes the missing piece. And touch is one of the hardest unsolved problems in physical AI.

In this episode of The Thinking Machine, I sit down with Tao Yu, Director of Dexterous AI Group at Analog Devices, to unpack why ADI is now building a humanoid hand platform with tactile sensing at its core.

Here are just a few topics get into:

- Why dexterous manipulation is the "crown jewel" of robotics, and why it's a hardware + sensor + data + AI problem all at once

- What tactile sensing actually involves: pressure, vibration, temperature, and the multimodal fusion problem

- Taxels (tactile pixels) and how human skin's ~1mm resolution sets the bar for fingertip sensors

- Why collecting good manipulation data is so hard when the human operator can't feel what the robot feels

- Real2Sim2Real with physics as the interface: how ADI thinks about modeling sensor non-idealities so policies trained in simulation actually transfer

About Tao Yu:
Tao Yu is the Director of Dexterous AI Group at Analog Devices, Inc. (ADI), where he leads research on multimodal tactile sensing for robotics and Physical AI. His work sits at the intersection of ADI's 60-year analog semiconductor heritage and the emerging demand for production-grade tactile sensors in dexterous manipulation and humanoid robotics.

Tao holds a PhD from MIT and has published research spanning tactile sensing, wireless sensor platforms, and signal processing. At ADI, he and his team are pioneering industrial-grade tactile sensors that capture force, vibration, and temperature at sub-millimeter resolution, as well as Physical AI research on tactile-enabled dexterous manipulation.

Tao on LinkedIn: linkedin.com/in/taoyumit/

Thanks to Lightwheel for making this episode possible.
Learn about how Lightwheel is making physical AI successful at https://lightwheel.ai

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The Thinking MachineBy Jonathan Stephens