4 citations · 4 across the 6 of their papers we have counts for
7 papers
Assessing the Marginal Utility of Exocentric Head Views in UMI-Style Large-FoV Wrist-Camera Manipulation
Yuhui Duan, Shi Jin, Yuntian Wang +5
Multi-view perception is often treated as a safe design choice for robot manipulation: if one camera is useful, more cameras should be better. We revisit that assumption in tableto…
UMI-Bench 1.0: An Open and Reproducible Real-World Benchmark for Tabletop Robotic Manipulation with UMI Data
Shi Jin, Yuntian Wang, Yuhui Duan +16
Real-robot evaluation is essential for understanding whether learned manipulation policies can operate reliably outside curated demonstrations. This need is particularly pressing f…
RT-Grasp: Reasoning Tuning Robotic Grasping via Multi-modal Large Language Model
Jinxuan Xu, Shiyu Jin, Yutian Lei +2
Recent advances in Large Language Models (LLMs) have showcased their remarkable reasoning capabilities, making them influential across various fields. However, in robotics, their u…
ExACT: An End-to-End Autonomous Excavator System Using Action Chunking With Transformers
Liangliang Chen, Shiyu Jin, Haoyu Wang +1
Excavators are crucial for diverse tasks such as construction and mining, while autonomous excavator systems enhance safety and efficiency, address labor shortages, and improve hum…
VIHE: Virtual In-Hand Eye Transformer for 3D Robotic Manipulation
Weiyao Wang, Yutian Lei, Shiyu Jin +2
In this work, we introduce the Virtual In-Hand Eye Transformer (VIHE), a novel method designed to enhance 3D manipulation capabilities through action-aware view rendering. VIHE aut…
RLingua: Improving Reinforcement Learning Sample Efficiency in Robotic Manipulations With Large Language Models
Liangliang Chen, Yutian Lei, Shiyu Jin +2
Reinforcement learning (RL) has demonstrated its capability in solving various tasks but is notorious for its low sample efficiency. In this paper, we propose RLingua, a framework…
Reasoning Grasping via Multimodal Large Language Model
Shiyu Jin, Jinxuan Xu, Yutian Lei +1
Despite significant progress in robotic systems for operation within human-centric environments, existing models still heavily rely on explicit human commands to identify and manip…