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ALOHA 2 is an enhanced low-cost reference design for bimanual teleoperation and imitation-learning data collection, sold as kits by Trossen Robotics. A stationary tabletop rig pairs two low-cost leader arms with two follower arms (6-DOF each) for leader-follower puppeteering, adding low-friction rail grippers, passive gravity compensation, and Intel RealSense D405 depth cameras. It ships with a high-fidelity MuJoCo model and open-source hardware, and underpins large-scale imitation/VLA datasets and Google DeepMind's Gemini Robotics demos.
Est. ~$32,000; config-dependent, typically $25k-40k for the full bimanual kit
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ALOHA 2 is the second-generation, open-source reference platform for A Low-cost Open-source Hardware System for Bimanual Teleoperation, originating from Stanford and Google DeepMind and commercialized as buildable kits by Trossen Robotics. The station is a stationary tabletop setup with two 6-DOF leader arms (WidowX-class) and two 6-DOF follower arms (ViperX-class); an operator back-drives the leaders to puppeteer the followers, capturing demonstrations for imitation learning and vision-language-action policies. Version 2 improvements over the original ALOHA include a redesigned low-friction rail gripper for both leader and follower, passive gravity compensation, more repeatable joints, and a switch to the compact Intel RealSense D405 depth cameras. A high-fidelity MuJoCo simulation model and open hardware make it a common benchmark platform for scaled robot-learning data collection.
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