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Microduck represents a significant milestone in accessible robotics by democratizing the full sim-to-real reinforcement learning loop for under $400. By providing open-source training stacks and pre-trained neural policies, it lowers the barrier to entry for researchers and hobbyists to experiment with bipedal locomotion and self-recovery algorithms. This shift from closed demos to open training environments accelerates practical advancements in embodied AI beyond theoretical research.
Hugging Face Unveils Microduck: A $399 Open-Source 25 cm Biped You Train with Reinforcement Learning
Pollen Robotics, the Bordeaux robotics team at Hugging Face, opened pre-orders for Microduck — a 25 cm bipedal robot where every movement is a neural policy trained in MuJoCo and exported to ONNX. At $399, it puts the full sim-to-real loop on a desk: 15 motors, camera, LiDAR, two IMUs, and an Apache-2.0 training stack you can retrain yourself. The post Hugging Face Unveils Microduck: A $399 Open-Source 25 cm Biped You Train with Reinforcement Learning appeared first on MarkTechPost.
Most robotics launches ask you to trust a demo video. Pollen Robotics, the Bordeaux robotics team at Hugging Face, is instead shipping the training loop. This week it opened pre-orders for Microduck, a 25 cm bipedal robot in which every movement — walking, sitting, kicking, roller-skating, standing back up after a fall — is a neural policy trained in a physics simulator and exported…
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