8 citations · 19 across the 18 of their papers we have counts for
18 papers
GaP: A Graph-as-Policy Multi-Agent Self-Learning Harness For Variational Automation Tasks
Kaiyuan Chen, Shuangyu Xie, Letian Fu +21
For robots to work reliably in commercial and industrial applications, can recent advances in agentic coding systems combine interpretable robot programming with the open-world ada…
ASPIRE: Agentic /Skills Discovery for Robotics
Runyu Lu, Yubo Wu, Ethan Kou +13
Traditional robot programming is notoriously challenging: it requires orchestrating multimodal perception, managing physical contact dynamics, and handling diverse environment conf…
T-Rex: Tactile-Reactive Dexterous Manipulation
Dantong Niu, Zhuoyang Liu, Zekai Wang +31
The ability to react dynamically to tactile signals has long been considered crucial to agile human-level dexterity. Yet contemporary learning-based Vision-Language-Action (VLA) mo…
Playful Agentic Robot Learning
Junyi Zhang, Jiaxin Ge, Hanjun Yoo +17
Current agentic robot systems can write executable Code-as-Policy programs, observe feedback, and revise behavior across multiple attempts, but they remain largely task-driven: reu…
EgoScale: Scaling Dexterous Manipulation with Diverse Egocentric Human Data
Ruijie Zheng, Dantong Niu, Yuqi Xie +12
Human behavior is among the most scalable sources of data for learning physical intelligence, yet how to effectively leverage it for dexterous manipulation remains unclear. While p…
VisGym: Diverse, Customizable, Scalable Environments for Multimodal Agents
Zirui Wang, Junyi Zhang, Jiaxin Ge +9
Modern Vision-Language Models (VLMs) remain poorly characterized in multi-step visual interactions, particularly in how they integrate perception, memory, and action over long hori…
Robo-DM: Data Management For Large Robot Datasets
Kaiyuan Chen, Letian Fu, David Huang +9
Recent results suggest that very large datasets of teleoperated robot demonstrations can be used to train transformer-based models that have the potential to generalize to new scen…
Real2Render2Real: Scaling Robot Data Without Dynamics Simulation or Robot Hardware
Justin Yu, Letian Fu, Huang Huang +5
Scaling robot learning requires vast and diverse datasets. Yet the prevailing data collection paradigm-human teleoperation-remains costly and constrained by manual effort and physi…
OTTER: A Vision-Language-Action Model with Text-Aware Visual Feature Extraction
Huang Huang, Fangchen Liu, Letian Fu +5
Vision-Language-Action (VLA) models aim to predict robotic actions based on visual observations and language instructions. Existing approaches require fine-tuning pre-trained visio…
Blox-Net: Generative Design-for-Robot-Assembly Using VLM Supervision, Physics Simulation, and a Robot with Reset
Andrew Goldberg, Kavish Kondap, Tianshuang Qiu +7
Generative AI systems have shown impressive capabilities in creating text, code, and images. Inspired by the rich history of research in industrial ''Design for Assembly'', we intr…
Lifelong LERF: Local 3D Semantic Inventory Monitoring Using FogROS2
Adam Rashid, Chung Min Kim, Justin Kerr +11
Inventory monitoring in homes, factories, and retail stores relies on maintaining data despite objects being swapped, added, removed, or moved. We introduce Lifelong LERF, a method…
A Touch, Vision, and Language Dataset for Multimodal Alignment
Letian Fu, Gaurav Datta, Huang Huang +7
Touch is an important sensing modality for humans, but it has not yet been incorporated into a multimodal generative language model. This is partially due to the difficulty of obta…
Rethinking Patch Dependence for Masked Autoencoders
Letian Fu, Long Lian, Renhao Wang +6
In this work, we examine the impact of inter-patch dependencies in the decoder of masked autoencoders (MAE) on representation learning. We decompose the decoding mechanism for mask…
Robot Learning with Sensorimotor Pre-training
Ilija Radosavovic, Baifeng Shi, Letian Fu +3
We present a self-supervised sensorimotor pre-training approach for robotics. Our model, called RPT, is a Transformer that operates on sequences of sensorimotor tokens. Given a seq…
Safe Self-Supervised Learning in Real of Visuo-Tactile Feedback Policies for Industrial Insertion
Letian Fu, Huang Huang, Lars Berscheid +3
Industrial insertion tasks are often performed repetitively with parts that are subject to tight tolerances and prone to breakage. Learning an industrial insertion policy in real i…
Mechanical Search on Shelves with Efficient Stacking and Destacking of Objects
Huang Huang, Letian Fu, Michael Danielczuk +6
Stacking increases storage efficiency in shelves, but the lack of visibility and accessibility makes the mechanical search problem of revealing and extracting target objects diffic…
Mechanical Search on Shelves using a Novel "Bluction" Tool
Huang Huang, Michael Danielczuk, Chung Min Kim +6
Shelves are common in homes, warehouses, and commercial settings due to their storage efficiency. However, this efficiency comes at the cost of reduced visibility and accessibility…
LEGS: Learning Efficient Grasp Sets for Exploratory Grasping
Letian Fu, Michael Danielczuk, Ashwin Balakrishna +4
While deep learning has enabled significant progress in designing general purpose robot grasping systems, there remain objects which still pose challenges for these systems. Recent…