Idan Shenfeld

May 10, 2024 | arxiv.org | Idan Shenfeld |Akash Srivastava |Yoon Kim |Pulkit Agrawal

arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.

Apr 4, 2024 | arxiv.org | Anthony Simeonov |Pulkit Agrawal |Idan Shenfeld

[Submitted on 4 Apr 2024] Title:JUICER: Data-Efficient Imitation Learning for Robotic Assembly View a PDF of the paper titled JUICER: Data-Efficient Imitation Learning for Robotic Assembly, by Lars Ankile and Anthony Simeonov and Idan Shenfeld and Pulkit Agrawal View PDF HTML (experimental) Abstract:While learning from demonstrations is powerful for acquiring visuomotor policies, high-performance imitation without large demonstration datasets remains challenging for tasks requiring precise,...