TR2024-033
Multi-level Reasoning for Robotic Assembly: From Sequence Inference to Contact Selection
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- "Multi-level Reasoning for Robotic Assembly: From Sequence Inference to Contact Selection", IEEE International Conference on Robotics and Automation (ICRA), March 2024.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,
- month = mar,
- url = {https://www.merl.com/publications/TR2024-033}
- }
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- "Multi-level Reasoning for Robotic Assembly: From Sequence Inference to Contact Selection", IEEE International Conference on Robotics and Automation (ICRA), March 2024.
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MERL Contacts:
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Research Areas:
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.
Related News & Events
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NEWS Diego Romeres gave an invited talk at the Padua University's Seminar series on "AI in Action" Date: April 9, 2024
MERL Contact: Diego Romeres
Research Areas: Artificial Intelligence, Dynamical Systems, Machine Learning, Optimization, RoboticsBrief- Diego Romeres, Principal Research Scientist and Team Leader in the Optimization and Robotics Team, was invited to speak as a guest lecturer in the seminar series on "AI in Action" in the Department of Management and Engineering, at the University of Padua.
The talk, entitled "Machine Learning for Robotics and Automation" described MERL's recent research on machine learning and model-based reinforcement learning applied to robotics and automation.
- Diego Romeres, Principal Research Scientist and Team Leader in the Optimization and Robotics Team, was invited to speak as a guest lecturer in the seminar series on "AI in Action" in the Department of Management and Engineering, at the University of Padua.
Related Video
Related Publication
- @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}
- }