Why Robot Arms Still Can't Peel a Potato

Lucas and Luna dig into one of robotics' most stubborn problems: dextrous manipulation of soft, irregular objects. They focus on why peeling a potato is surprisingly harder than assembling a car, and how a team at Carnegie Mellon used a $200 force sensor and a lot of machine learning to get closer. The episode covers the physics of variable stiffness, the limits of current grippers, and why a simple kitchen task remains a benchmark for robotic dexterity. Listeners will walk away understanding why your Roomba won't be making dinner anytime soon. #Robotics #Manipulation #DextrousRobotics #SoftRobotics #CarnegieMellon #ForceSensing #MachineLearning #PotatoPeeling #IndustrialRobots #AutonomousSystems #RobotGrippers #TactileSensing #Technology #FexingoBusiness #BusinessPodcast #RoboticsPodcast #Hardware #Automation Keep every episode free: buymeacoffee.com/fexingo