Duet 2 : Bimanual VLA Manipulation

Duet 2 explores how two low-cost SO-101 robot arms can coordinate as one bimanual Physical AI system. In a MuJoCo dinner-table environment, the arms work together to pick, transfer, place, and manipulate everyday objects such as a plate, mug, bottle, fork, and spoon across randomized scene layouts. The project has two clearly separated layers. First, a verified expert-teacher policy demonstrates the complete physical workflow using contact and placement checks, producing reproducible trajectories and training data. Second, a real SmolVLA vision-language-action model is fine-tuned on those demonstrations and runs from camera images, natural-language instructions, and robot state. The live VLA is intentionally presented as an experimental research result rather than a scripted fallback. Duet 2 also focuses on practical AI infrastructure. The model pipeline uses LeRobot and Hugging Face, while the vision tower is accelerated with Intel OpenVINO on CPU. On an Intel Core i5-8265U baseline, optimization improved end-to-end real-time factor from 0.05 to 0.49, a 10.3× speedup, while preserving parity for the OpenVINO vision path. The project includes deterministic seeds, recorded demonstrations, replayable evidence, a judge-facing web dashboard, and a reproducible open-source pipeline for data collection, training, benchmarking, and deployment.