Remarkable progress has been made in recent years in the fields of vision, language, and
robotics. We now have vision models capable of recognizing objects based on language …

Performing language-conditioned robotic manipulation tasks in unstructured environments
is highly demanded for general intelligent robots. Conventional robotic manipulation …

Teleoperation is a crucial tool for collecting human demonstrations, but controlling robots
with bimanual dexterous hands remains a challenge. Existing teleoperation systems …

We present RoboGen, a generative robotic agent that automatically learns diverse robotic
skills at scale via generative simulation. RoboGen leverages the latest advancements in …

We present ChainedDiffuser, a policy architecture that unifies action keypose prediction and
trajectory diffusion generation for learning robot manipulation from demonstrations. Our …

We present GR-2, a state-of-the-art generalist robot agent for versatile and generalizable
robot manipulation. GR-2 is first pre-trained on a vast number of Internet videos to capture …

Abstract This paper introduces Hierarchical Diffusion Policy (HDP) a hierarchical agent for
multi-task robotic manipulation. HDP factorises a manipulation policy into a hierarchical …

Scene representation has been a crucial design choice in robotic manipulation systems. An
ideal representation should be 3D, dynamic, and semantic to meet the demands of diverse …

Generalist robot manipulators need to learn a wide variety of manipulation skills across
diverse environments. Current robot training pipelines rely on humans to provide kinesthetic …

Learning generalizable visual representations from Internet data has yielded promising
results for robotics. Yet prevailing approaches focus on pre-training 2D representations …