Pierre Rouanet, co-founder of Pollen Robotics, discusses how AI is changing robotics and what it will take to bring useful robots into homes and workplaces, speaking at a PyTorch event.
Rouanet draws on about a decade building humanoid robots and other robotic systems. He describes a shift from factory automation, where tasks and surroundings are fixed, toward robots that must adapt and interact in everyday environments.
Vision and language models help robots recognize varied objects and respond to context; a robot could interpret an instruction to pick up an orange and put it in a brown bag. Deep reinforcement learning paired with realistic simulation has also helped humanoids walk, run, and jump, while narrowing the gap between simulation and real hardware.
Rouanet argues that cleaning a kitchen can be harder for robots than acrobatic movement because objects and room layouts vary, and there is no single correct sequence of actions. A kitchen task may require planning tens of seconds or a minute ahead, beyond the short horizons used for locomotion.
He says progress likely depends on more first-person, responsive data that captures physical interaction, rather than relying only on static videos scraped from the internet. Robot fleets and teleoperation can collect this data, but scaling to potentially millions of examples is difficult; simulation and human demonstrations also face transfer gaps.
Rouanet says hardware costs, maintenance, and safety can keep robotics research confined to large labs and companies. He highlights a low-cost manipulator with printable plans, parts lists, compatible software, and a T-shirt-folding tutorial, plus an accessible locomotion robot whose simulated policy can run on real hardware.
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Pierre Rouanet, co-founder and CTO of Pollen Robotics, and Elsa Kervella, the company’s marketing and sales lead, discuss Reachy’s manipulation, design and development at Pollen Robotics.
