TR2024-033

Multi-level Reasoning for Robotic Assembly: From Sequence Inference to Contact Selection


    •  Zhu, X., Jha, D.K., Romeres, D., Sun, L., Tomizuka, M., Cherian, A., "Multi-level Reasoning for Robotic Assembly: From Sequence Inference to Contact Selection", IEEE International Conference on Robotics and Automation (ICRA), March 2024, pp. 816-823.
      BibTeX TR2024-033 PDF Video
      • @inproceedings{Zhu2024mar,
      • author = {Zhu, Xinghao and Jha, Devesh K. and Romeres, Diego and Sun, Lingfeng and Tomizuka, Masayoshi and Cherian, Anoop},
      • title = {Multi-level Reasoning for Robotic Assembly: From Sequence Inference to Contact Selection},
      • booktitle = {IEEE International Conference on Robotics and Automation (ICRA)},
      • year = 2024,
      • pages = {816--823},
      • month = mar,
      • publisher = {IEEE},
      • url = {https://www.merl.com/publications/TR2024-033}
      • }
  • MERL Contacts:
  • Research Areas:

    Artificial Intelligence, Machine Learning, Robotics

Abstract:

Automating the assembly of objects from their parts is a complex problem with innumerable applications in manufacturing, maintenance, and recycling. Unlike existing re- search, which is limited to target segmentation, pose regression, or using fixed target blueprints, our work presents a holistic multi-level framework for part assembly planning consisting of part assembly sequence inference, part motion planning, and robot contact optimization. We present the Part Assembly Sequence Transformer (PAST) – a sequence-to-sequence neural network – to infer assembly sequences recursively from a target blueprint. We then use a motion planner and optimization to generate part movements and contacts. To train PAST, we introduce D4PAS: a large-scale Dataset for Part Assembly Sequences consisting of physically valid sequences for industrial objects. Experimental results show that our approach generalizes better than prior methods while needing significantly less computational time for inference. Further details on our experiments and results are available in the video.

 

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  •  Zhu, X., Jha, D.K., Romeres, D., Sun, L., Tomizuka, M., Cherian, A., "Multi-level Reasoning for Robotic Assembly: From Sequence Inference to Contact Selection", arXiv, December 2023.
    BibTeX arXiv
    • @article{Zhu2023dec,
    • author = {Zhu, Xinghao and Jha, Devesh K. and Romeres, Diego and Sun, Lingfeng and Tomizuka, Masayoshi and Cherian, Anoop},
    • title = {Multi-level Reasoning for Robotic Assembly: From Sequence Inference to Contact Selection},
    • journal = {arXiv},
    • year = 2023,
    • month = dec,
    • url = {https://arxiv.org/abs/2312.10571}
    • }