Hands-on Physical AI with Kevin Cloutier

Kevin Cloutier is the North American Lead for Physical AI at CapGemini , a global engineering consulting firm. He is a computer engineer who is passionate about taking complex computations to the edge. He joins Chris to discuss the transition from legacy, statically programmed factory robotics to modern, imitation-learning-based “Physical AI,” building and calibrating the affordable $200 3D-printed SO101 robot arm using the LeRobot open-source framework or Intel’s Physical AI Studio , and orchestrating complex robotic systems entirely on local edge hardware. Timeline Chris welcomes Kevin Cloutier to discuss “Physical AI” and how it relates to robots and things that move in the physical world. (00:00:15) Meeting at Embedded World: They reminisce about meeting at the Canonical booth in front of a robot demonstration, which you can see in the Embedded World Demonstration Video . (00:02:10) Trade Shows and Geography: Chris and Kevin discuss Embedded World in Nuremberg, Germany, upcoming SPS, and the high concentration of manufacturing robots in Europe compared to the US. (00:03:50) The “Unicorn Developer” Shift: Kevin talks about his background in computer engineering and how the “unicorn developer” has shifted from the full-stack web developer of the 1990s to someone who can operate, program, repair, and train physical robots. (00:06:05) Factory Robots vs. Edge Cases: Contrasting legacy, statically programmed factory robots (like ABB or Universal Robots hanging car doors) with modern generative AI approaches capable of handling real-world edge cases. (00:09:15) The Robotics Software Stack: Demystifying the layers above motor drivers, including Real-Time Operating Systems (RTOS), Linux, and message-passing frameworks like ROS (Robot Operating System) and ROS 2. (00:12:40) Orchestrating Systems of Systems: Kevin describes playing tic-tac-toe using Vision Language Action (VLA) models , where a higher-level camera and computer vision system orchestrate the coordinates for the movement model. (00:15:10) The Evolution of Compute: How modern silicon, integrated GPUs, and SOCs have allowed the massive, heavy control boxes of legacy robots to shrink down to a small NUC-sized device mounted directly on the robot. (00:18:05) The SO101 Robot Arm: Introducing the SO101 3D-printed robot arm from Hugging Face , which democratizes robotics by allowing anyone to build a leader-follower setup for around $200. (00:21:20) How “Backyard Engineers” Learn: Kevin’s advice for firmware and hardware engineers stepping into robotics: follow the documentation, get it running, and then ask questions about what you don’t know. (00:23:55) Calibration and the LeRobot Framework: A look at using the LeRobot open-source framework to calibrate hobby-grade motors and define their movement limits. (00:26:40) Recording “Episodes” via Imitation Learning: How users physically guide the leader arm to control the follower arm while a webcam records the visual and servo coordinate data. (00:28:50) Training the Model: Organizing data into short 5-episode chunks to make deletion easier, and training the model locally on NVIDIA GPUs or in the cloud. (00:31:30) From Training to Evaluation: Moving from training