We introduce BridgeData V2, a large and diverse dataset of robotic
manip...
We study the problem of learning to perform multi-stage robotic manipula...
Our goal is for robots to follow natural language instructions like "put...
In the same way that the computer vision (CV) and natural language proce...
Solving real-world sequential manipulation tasks requires robots to have...
The utilization of broad datasets has proven to be crucial for generaliz...
General-purpose robots require diverse repertoires of behaviors to compl...
The learning efficiency and generalization ability of an intelligent age...
Search engine has become a fundamental component in various web and mobi...
We introduce Adaptive Procedural Task Generation (APT-Gen), an approach ...
Learning-to-rank (LTR) is a set of supervised machine learning algorithm...
The fundamental challenge of planning for multi-step manipulation is to ...
We aim to develop an algorithm for robots to manipulate novel objects as...
Many robotic applications require the agent to perform long-horizon task...
Tool manipulation is vital for facilitating robots to complete challengi...
The main challenge of online multi-object tracking is to reliably associ...
Learning-based approaches to robotic manipulation are limited by the
sca...