52 citations · 194 across the 16 of their papers we have counts for
14 papers · 1 filter
DexTaG: Tactile-as-Guidance in Reinforcement Learning for Dexterous Manipulation
Han Yang, Yian Wang, Yunlong Song +2
Glove-based motion capture is emerging as a scalable approach to collecting dexterous-hand demonstration data. However, due to the kinematic gap between the human and robot hand, t…
Flow as the Cross-Domain Manipulation Interface
Mengda Xu, Zhenjia Xu, Yinghao Xu +4
We present Im2Flow2Act, a scalable learning framework that enables robots to acquire real-world manipulation skills without the need of real-world robot training data. The key idea…
Universal Manipulation Interface: In-The-Wild Robot Teaching Without In-The-Wild Robots
Cheng Chi, Zhenjia Xu, Chuer Pan +5
We present Universal Manipulation Interface (UMI) -- a data collection and policy learning framework that allows direct skill transfer from in-the-wild human demonstrations to depl…
XSkill: Cross Embodiment Skill Discovery
Mengda Xu, Zhenjia Xu, Cheng Chi +2
Human demonstration videos are a widely available data source for robot learning and an intuitive user interface for expressing desired behavior. However, directly extracting reusa…
Robots That Ask For Help: Uncertainty Alignment for Large Language Model Planners
Allen Z. Ren, Anushri Dixit, Alexandra Bodrova +11
Large language models (LLMs) exhibit a wide range of promising capabilities -- from step-by-step planning to commonsense reasoning -- that may provide utility for robots, but remai…
Towards Generalist Robots: A Promising Paradigm via Generative Simulation
Zhou Xian, Theophile Gervet, Zhenjia Xu +3
This document serves as a position paper that outlines the authors' vision for a potential pathway towards generalist robots. The purpose of this document is to share the excitemen…
FluidLab: A Differentiable Environment for Benchmarking Complex Fluid Manipulation
Zhou Xian, Bo Zhu, Zhenjia Xu +4
Humans manipulate various kinds of fluids in their everyday life: creating latte art, scooping floating objects from water, rolling an ice cream cone, etc. Using robots to augment…
Diffusion Policy: Visuomotor Policy Learning via Action Diffusion
Cheng Chi, Zhenjia Xu, Siyuan Feng +5
This paper introduces Diffusion Policy, a new way of generating robot behavior by representing a robot's visuomotor policy as a conditional denoising diffusion process. We benchmar…
RoboNinja: Learning an Adaptive Cutting Policy for Multi-Material Objects
Zhenjia Xu, Zhou Xian, Xingyu Lin +4
We introduce RoboNinja, a learning-based cutting system for multi-material objects (i.e., soft objects with rigid cores such as avocados or mangos). In contrast to prior works usin…
BusyBot: Learning to Interact, Reason, and Plan in a BusyBoard Environment
Zeyi Liu, Zhenjia Xu, Shuran Song
We introduce BusyBoard, a toy-inspired robot learning environment that leverages a diverse set of articulated objects and inter-object functional relations to provide rich visual f…
DextAIRity: Deformable Manipulation Can be a Breeze
Zhenjia Xu, Cheng Chi, Benjamin Burchfiel +3
This paper introduces DextAIRity, an approach to manipulate deformable objects using active airflow. In contrast to conventional contact-based quasi-static manipulations, DextAIRit…
Learning 3D Dynamic Scene Representations for Robot Manipulation
Zhenjia Xu, Zhanpeng He, Jiajun Wu +1
3D scene representation for robot manipulation should capture three key object properties: permanency -- objects that become occluded over time continue to exist; amodal completene…
AdaGrasp: Learning an Adaptive Gripper-Aware Grasping Policy
Zhenjia Xu, Beichun Qi, Shubham Agrawal +1
This paper aims to improve robots' versatility and adaptability by allowing them to use a large variety of end-effector tools and quickly adapt to new tools. We propose AdaGrasp, a…
DensePhysNet: Learning Dense Physical Object Representations via Multi-step Dynamic Interactions
Zhenjia Xu, Jiajun Wu, Andy Zeng +2
We study the problem of learning physical object representations for robot manipulation. Understanding object physics is critical for successful object manipulation, but also chall…