1 citations · 2 across the 15 of their papers we have counts for
17 papers
Pix2Act: Image-Space Manipulation Policies with Equivariant Augmentation
Haojie Huang, Linfeng Zhao, Haotian Liu +9
Representing manipulation actions as 2D trajectories in the camera plane provides a compact and interpretable basis for learning complex 3D manipulation policies. However, it also…
Action Map Policy: Learning 3D Closed-loop Manipulation via Pixel Classification
Haojie Huang, Zhang Ye, Linfeng Zhao +7
The action space poses a major challenge in robot learning, since it is often high-dimensional, can span long time horizons, and frequently admits multi-modal optimal solutions. A…
When Life Gives You BC, Make Q-functions: Extracting Q-values from Behavior Cloning for On-Robot Reinforcement Learning
Lakshita Dodeja, Ondrej Biza, Shivam Vats +5
Behavior Cloning (BC) has emerged as a highly effective paradigm for robot learning. However, BC lacks a self-guided mechanism for online improvement after demonstrations have been…
You've Got a Golden Ticket: Improving Generative Robot Policies With A Single Noise Vector
Omkar Patil, Ondrej Biza, Thomas Weng +9
Generative robot policies trained on demonstrations using behavior cloning often learn actions that are sub-optimal or misaligned with respect to the downstream task. Policy improv…
Generalizable Hierarchical Skill Learning via Object-Centric Representation
Haibo Zhao, Yu Qi, Boce Hu +9
We present Generalizable Hierarchical Skill Learning (GSL), a novel framework for hierarchical policy learning that significantly improves policy generalization and sample efficien…
Clebsch-Gordan Transformer: Fast and Global Equivariant Attention
Owen Lewis Howell, Linfeng Zhao, Xupeng Zhu +6
The global attention mechanism is one of the keys to the success of transformer architecture, but it incurs quadratic computational costs in relation to the number of tokens. On th…
SE(3)-Equivariant Diffusion Policy in Spherical Fourier Space
Xupeng Zhu, Fan Wang, Robin Walters +1
Diffusion Policies are effective at learning closed-loop manipulation policies from human demonstrations but generalize poorly to novel arrangements of objects in 3D space, hurting…
EquAct: An SE(3)-Equivariant Multi-Task Transformer for Open-Loop Robotic Manipulation
Xupeng Zhu, Yu Qi, Yizhe Zhu +2
Transformer architectures can effectively learn language-conditioned, multi-task 3D open-loop manipulation policies from demonstrations by jointly processing natural language instr…
3D Equivariant Visuomotor Policy Learning via Spherical Projection
Boce Hu, Dian Wang, David Klee +5
Equivariant models have recently been shown to improve the data efficiency of diffusion policy by a significant margin. However, prior work that explored this direction focused pri…
A Practical Guide for Incorporating Symmetry in Diffusion Policy
Dian Wang, Boce Hu, Shuran Song +2
Recently, equivariant neural networks for policy learning have shown promising improvements in sample efficiency and generalization, however, their wide adoption faces substantial…
Push-Grasp Policy Learning Using Equivariant Models and Grasp Score Optimization
Boce Hu, Heng Tian, Dian Wang +4
Goal-conditioned robotic grasping in cluttered environments remains a challenging problem due to occlusions caused by surrounding objects, which prevent direct access to the target…
Hierarchical Equivariant Policy via Frame Transfer
Haibo Zhao, Dian Wang, Yizhe Zhu +6
Recent advances in hierarchical policy learning highlight the advantages of decomposing systems into high-level and low-level agents, enabling efficient long-horizon reasoning and…
Coarse-to-Fine 3D Keyframe Transporter
Xupeng Zhu, David Klee, Dian Wang +5
Recent advances in Keyframe Imitation Learning (IL) have enabled learning-based agents to solve a diverse range of manipulation tasks. However, most approaches ignore the rich symm…
MATCH POLICY: A Simple Pipeline from Point Cloud Registration to Manipulation Policies
Haojie Huang, Haotian Liu, Dian Wang +2
Many manipulation tasks require the robot to rearrange objects relative to one another. Such tasks can be described as a sequence of relative poses between parts of a set of rigid…
OrbitGrasp: -Equivariant Grasp Learning
Boce Hu, Xupeng Zhu, Dian Wang +5
While grasp detection is an important part of any robotic manipulation pipeline, reliable and accurate grasp detection in remains a research challenge. Many robotics applic…
Learning Efficient and Robust Language-conditioned Manipulation using Textual-Visual Relevancy and Equivariant Language Mapping
Mingxi Jia, Haojie Huang, Zhewen Zhang +7
Controlling robots through natural language is pivotal for enhancing human-robot collaboration and synthesizing complex robot behaviors. Recent works that are trained on large robo…
Imagination Policy: Using Generative Point Cloud Models for Learning Manipulation Policies
Haojie Huang, Karl Schmeckpeper, Dian Wang +6
Humans can imagine goal states during planning and perform actions to match those goals. In this work, we propose Imagination Policy, a novel multi-task key-frame policy network fo…