Web: http://arxiv.org/abs/2202.09400

Sept. 23, 2022, 1:15 a.m. | Haojie Huang, Dian Wang, Robin Walters, Robert Platt

cs.CV updates on arXiv.org arxiv.org

Transporter Net is a recently proposed framework for pick and place that is
able to learn good manipulation policies from a very few expert demonstrations.
A key reason why Transporter Net is so sample efficient is that the model
incorporates rotational equivariance into the pick module, i.e. the model
immediately generalizes learned pick knowledge to objects presented in
different orientations. This paper proposes a novel version of Transporter Net
that is equivariant to both pick and place orientation. As a …

arxiv network

More from arxiv.org / cs.CV updates on arXiv.org

Research Scientists

@ ODU Research Foundation | Norfolk, Virginia

Embedded Systems Engineer (Robotics)

@ Neo Cybernetica | Bedford, New Hampshire

2023 Luis J. Alvarez and Admiral Grace M. Hopper Postdoc Fellowship in Computing Sciences

@ Lawrence Berkeley National Lab | San Francisco, CA

Senior Manager Data Scientist

@ NAV | Remote, US

Senior AI Research Scientist

@ Earth Species Project | Remote anywhere

Research Fellow- Center for Security and Emerging Technology (Multiple Opportunities)

@ University of California Davis | Washington, DC

Staff Fellow - Data Scientist

@ U.S. FDA/Center for Devices and Radiological Health | Silver Spring, Maryland

Staff Fellow - Senior Data Engineer

@ U.S. FDA/Center for Devices and Radiological Health | Silver Spring, Maryland

Tech Business Data Analyst

@ Fivesky | Alpharetta, GA

Senior Applied Scientist

@ Amazon.com | London, England, GBR

AI Researcher (Junior/Mid-level)

@ Charles River Analytics Inc. | Cambridge, MA

Data Engineer - Machine Learning & AI

@ Calabrio | Minneapolis, Minnesota, United States