no code implementations • 7 Jun 2019 • Allan Zhou, Eric Jang, Daniel Kappler, Alex Herzog, Mohi Khansari, Paul Wohlhart, Yunfei Bai, Mrinal Kalakrishnan, Sergey Levine, Chelsea Finn
Imitation learning allows agents to learn complex behaviors from demonstrations.
no code implementations • 25 Feb 2020 • Avi Singh, Eric Jang, Alexander Irpan, Daniel Kappler, Murtaza Dalal, Sergey Levine, Mohi Khansari, Chelsea Finn
In this work, we target this challenge, aiming to build an imitation learning system that can continuously improve through autonomous data collection, while simultaneously avoiding the explicit use of reinforcement learning, to maintain the stability, simplicity, and scalability of supervised imitation.
no code implementations • 13 May 2020 • Mohi Khansari, Daniel Kappler, Jianlan Luo, Jeff Bingham, Mrinal Kalakrishnan
Similar to computer vision problems, such as object detection, Action Image builds on the idea that object features are invariant to translation in image space.
no code implementations • ICLR 2020 • Allan Zhou, Eric Jang, Daniel Kappler, Alex Herzog, Mohi Khansari, Paul Wohlhart, Yunfei Bai, Mrinal Kalakrishnan, Sergey Levine, Chelsea Finn
Imitation learning allows agents to learn complex behaviors from demonstrations.
no code implementations • 4 Feb 2022 • Eric Jang, Alex Irpan, Mohi Khansari, Daniel Kappler, Frederik Ebert, Corey Lynch, Sergey Levine, Chelsea Finn
In this paper, we study the problem of enabling a vision-based robotic manipulation system to generalize to novel tasks, a long-standing challenge in robot learning.
no code implementations • 20 Sep 2022 • Boyuan Chen, Fei Xia, Brian Ichter, Kanishka Rao, Keerthana Gopalakrishnan, Michael S. Ryoo, Austin Stone, Daniel Kappler
Large language models (LLMs) have unlocked new capabilities of task planning from human instructions.
1 code implementation • 19 Sep 2018 • Hamza Merzic, Miroslav Bogdanovic, Daniel Kappler, Ludovic Righetti, Jeannette Bohg
While it is possible to learn grasping policies without contact sensing, our results suggest that contact feedback allows for a significant improvement of grasping robustness under object pose uncertainty and for objects with a complex shape.
1 code implementation • 20 Sep 2017 • Franziska Meier, Daniel Kappler, Stefan Schaal
The promise of learning to learn for robotics rests on the hope that by extracting some information about the learning process itself we can speed up subsequent similar learning tasks.
1 code implementation • 20 Nov 2015 • Raghudeep Gadde, Varun Jampani, Martin Kiefel, Daniel Kappler, Peter V. Gehler
We introduce a new 'bilateral inception' module that can be inserted in existing CNN architectures and performs bilateral filtering, at multiple feature-scales, between superpixels in an image.