11 citations · 13 across the 5 of their papers we have counts for
5 papers · 1 filter
Deep SE(3)-Equivariant Geometric Reasoning for Precise Placement Tasks
Ben Eisner, Yi Yang, Todor Davchev +3
Many robot manipulation tasks can be framed as geometric reasoning tasks, where an agent must be able to precisely manipulate an object into a position that satisfies the task from…
RoboTAP: Tracking Arbitrary Points for Few-Shot Visual Imitation
Mel Vecerik, Carl Doersch, Yi Yang +6
For robots to be useful outside labs and specialized factories we need a way to teach them new useful behaviors quickly. Current approaches lack either the generality to onboard ne…
S3K: Self-Supervised Semantic Keypoints for Robotic Manipulation via Multi-View Consistency
Mel Vecerik, Jean-Baptiste Regli, Oleg Sushkov +7
A robot's ability to act is fundamentally constrained by what it can perceive. Many existing approaches to visual representation learning utilize general-purpose training criteria,…
Scaling data-driven robotics with reward sketching and batch reinforcement learning
Serkan Cabi, Sergio Gómez Colmenarejo, Alexander Novikov +13
We present a framework for data-driven robotics that makes use of a large dataset of recorded robot experience and scales to several tasks using learned reward functions. We show h…
A Practical Approach to Insertion with Variable Socket Position Using Deep Reinforcement Learning
Mel Vecerik, Oleg Sushkov, David Barker +3
Insertion is a challenging haptic and visual control problem with significant practical value for manufacturing. Existing approaches in the model-based robotics community can be hi…