DINOBot: Robot Manipulation via Retrieval and Alignment with Vision Foundation Models
<|reference_start|>DINOBot: Robot Manipulation via Retrieval and Alignment with Vision Foundation Models: We propose DINOBot, a novel imitation learning framework for robot manipulation, which leverages the image-level and pixel-level capabilities of features extracted from Vision Transformers trained with DINO. When interacting with a novel object, DINOBot first uses these features to retrieve the most visually similar object experienced during human demonstrations, and then uses this object to align its end-effector with the novel object to enable effective interaction. Through a series of real-world experiments on everyday tasks, we show that exploiting both the image-level and pixel-level properties of vision foundation models enables unprecedented learning efficiency and generalisation. Videos and code are available at https://www.robot-learning.uk/dinobot.<|reference_end|>
@article{di palo2024dinobot:,
    title={DINOBot: Robot Manipulation via Retrieval and Alignment with Vision
  Foundation Models},
    author={Norman Di Palo and Edward Johns},
    journal={arXiv preprint arXiv:2402.13181},
    year={2024},
    archivePrefix={arXiv},
    eprint={2402.13181},
    primaryClass={cs.RO cs.LG}
}