Get our free extension to see links to code for papers anywhere online!

Chrome logo  Add to Chrome

Firefox logo Add to Firefox

Picture for Daniel Kappler

Daniel Kappler

AMD, MPI for Intelligent Systems, Tübingen, Germany, Lula Robotics Inc, Seattle, USA

Open-vocabulary Queryable Scene Representations for Real World Planning


Sep 20, 2022
Boyuan Chen, Fei Xia, Brian Ichter, Kanishka Rao, Keerthana Gopalakrishnan, Michael S. Ryoo, Austin Stone, Daniel Kappler

Add code


   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

BC-Z: Zero-Shot Task Generalization with Robotic Imitation Learning


Feb 04, 2022
Eric Jang, Alex Irpan, Mohi Khansari, Daniel Kappler, Frederik Ebert, Corey Lynch, Sergey Levine, Chelsea Finn

Add code

* Conference on Robot Learning (pp. 991-1002). 2022 Jan 11 
* CoRL 2021, 23 pages 

   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Action Image Representation: Learning Scalable Deep Grasping Policies with Zero Real World Data


May 13, 2020
Mohi Khansari, Daniel Kappler, Jianlan Luo, Jeff Bingham, Mrinal Kalakrishnan

Add code

* 7 pages, 10 figures, and 3 tables. To be published in International Conference on Robotics and Automation, 2020 

   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Scalable Multi-Task Imitation Learning with Autonomous Improvement


Feb 25, 2020
Avi Singh, Eric Jang, Alexander Irpan, Daniel Kappler, Murtaza Dalal, Sergey Levine, Mohi Khansari, Chelsea Finn

Add code

* Accepted to ICRA 2020. Supplementary material at https://sites.google.com/view/scalable-mili 

   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Watch, Try, Learn: Meta-Learning from Demonstrations and Reward


Jun 07, 2019
Allan Zhou, Eric Jang, Daniel Kappler, Alex Herzog, Mohi Khansari, Paul Wohlhart, Yunfei Bai, Mrinal Kalakrishnan, Sergey Levine, Chelsea Finn

Add code


   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Leveraging Contact Forces for Learning to Grasp


Sep 19, 2018
Hamza Merzic, Miroslav Bogdanovic, Daniel Kappler, Ludovic Righetti, Jeannette Bohg

Add code

* 7 pages, 5 figures, Submitted to ICRA'19 

   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Grasp success prediction with quality metrics


Sep 10, 2018
Carlos Rubert, Daniel Kappler, Jeannette Bohg, Antonio Morales

Add code


   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Riemannian Motion Policies


Jul 25, 2018
Nathan D. Ratliff, Jan Issac, Daniel Kappler, Stan Birchfield, Dieter Fox

Add code


   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Online Learning of a Memory for Learning Rates


Mar 23, 2018
Franziska Meier, Daniel Kappler, Stefan Schaal

Add code

* accepted to ICRA 2018, code available: https://github.com/fmeier/online-meta-learning ; video pitch available: https://youtu.be/9PzQ25FPPOM 

   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

A New Data Source for Inverse Dynamics Learning


Oct 06, 2017
Daniel Kappler, Franziska Meier, Nathan Ratliff, Stefan Schaal

Add code

* IROS 2017 

   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email
1
2
>>