Physical AI: The DARPA Legacy & the Road Ahead — From Face-Plants to Foundation Models
Part 1 of 2, Physical AI: The DARPA Legacy & the Road Ahead. What the DARPA Robotics Challenge Actually Built—and Why It Still...
Tactile-Based Robot Centering as a Capability for Dexterous Manipulation
A robot does not always grip a part exactly where intended. Vision may guide the gripper close, but camera calibration, part...
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How Robotiq Built the TSF-85 Tactile Sensor to the Spec of the Human Hand
Read the full technical article from Jennifer Kwiatkowski on Tech Brief.For teams building contact-rich manipulation, tactile...
Robotiq releases TSF-85 Tactile Sensor Digital Twin on NVIDIA Isaac Sim
Also read NVIDIA's COMPUTEX coverage, where Robotiq appears alongside the latest Isaac GR00T updates.
The economics of Physical AI: Why data quality beats scale
To reach the level of robustness the Physical AI community aspires to, namely generalist policies deployable zero-shot on...
How tactile sensing improves model performance
Vision-language-action models are the current state of the art in robotic manipulation. They still cannot pick up a potato chip...
Why Physical AI isn't scaling yet, and what's holding it back
Physical AI is advancing quickly.
AI models can now recognize objects, plan actions, and adapt to new tasks. But despite this...
AI can decide. But can it act? The missing layer in Physical AI
Artificial intelligence has made impressive progress.
Models can classify images, generate text, and even plan complex...
Scaling Physical AI: Why grippers and sensors matter for real-world robotics
Physical AI is evolving quickly.
From imitation learning to foundation models, robotics teams are making real progress toward...
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