Dobb-E is an open-source general framework designed for training and evaluating robotic manipulation skills in household environments. It provides tools for learning from demonstrations, including affordable hardware for easy data collection, a large-scale dataset of household tasks, and a pretrained model for rapid adaptation to new tasks. It's targeted at robotics researchers, developers, and academics interested in imitation learning and home robotics.
Visit Dobb-E's official website for product details and getting started.