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 …

Affordance grounding refers to the task of finding the area of an object with which one can
interact. It is a fundamental but challenging task as a successful solution requires the …

Large-scale endeavors like and widespread community efforts such as Open-X-Embodiment
have contributed to growing the scale of robot demonstration data. However, there is still an …

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

Abstract This paper proposes Retrieval-Enhanced Asymmetric Diffusion (READ) for image-
based robot motion planning. Given an image of the scene READ retrieves an initial motion …

Learning from Demonstrations, the field that proposes to learn robot behavior models from
data, is gaining popularity with the emergence of deep generative models. Although the …

Can we endow visuomotor robots with generalization capabilities to operate in diverse open-
world scenarios? In this paper, we propose\textbf {Maniwhere}, a generalizable framework …

We marry diffusion policies and 3D scene representations for robot manipulation. Diffusion
policies learn the action distribution conditioned on the robot and environment state using …

Many complex robotic manipulation tasks can be decomposed as a sequence of pick and
place actions. Training a robotic agent to learn this sequence over many different starting …