As robots become more prevalent, optimizing their design for better
perf...
Recent progress in end-to-end Imitation Learning approaches has shown
pr...
Learning from demonstration (LfD) is a proven technique to teach robots ...
In this work we investigate and demonstrate benefits of a Bayesian appro...
In this paper, we study the problem of enabling a vision-based robotic
m...
Recent work in visual end-to-end learning for robotics has shown the pro...
Robotic skills can be learned via imitation learning (IL) using user-pro...
The success of deep reinforcement learning (RL) and imitation learning (...
Deep neural network based reinforcement learning (RL) can learn appropri...
Complex object manipulation tasks often span over long sequences of
oper...
This paper introduces Action Image, a new grasp proposal representation ...
While robot learning has demonstrated promising results for enabling rob...
Training a deep network policy for robot manipulation is notoriously cos...
We propose a self-supervised approach for learning representations of ob...
Imitation learning allows agents to learn complex behaviors from
demonst...
We propose learning from teleoperated play data (LfP) as a way to scale ...
We propose a new non-parametric framework for learning incrementally sta...
This paper focuses on the problem of learning 6-DOF grasping with a para...