5 papers · 1 filter
OFlow: Injecting Object-Aware Temporal Flow Matching for Robust Robotic Manipulation
Kuanning Wang, Ke Fan, Chenhao Qiu +5
Robust robotic manipulation requires not only predicting how the scene evolves over time, but also recognizing task-relevant objects in complex scenes. However, existing VLA models…
OCRA: Object-Centric Learning with 3D and Tactile Priors for Human-to-Robot Action Transfer
Kuanning Wang, Ke Fan, Yuqian Fu +6
We present OCRA, an Object-Centric framework for video-based human-to-Robot Action transfer that learns directly from human demonstration videos to enable robust manipulation. Obje…
TP-MDDN: Task-Preferenced Multi-Demand-Driven Navigation with Autonomous Decision-Making
Shanshan Li, Da Huang, Yu He +3
In daily life, people often move through spaces to find objects that meet their needs, posing a key challenge in embodied AI. Traditional Demand-Driven Navigation (DDN) handles one…
SCOOP'D: Learning Mixed-Liquid-Solid Scooping via Sim2Real Generative Policy
Kuanning Wang, Yongchong Gu, Yuqian Fu +5
Scooping items with tools such as spoons and ladles is common in daily life, ranging from assistive feeding to retrieving items from environmental disaster sites. However, developi…
TriVLA: A Triple-System-Based Unified Vision-Language-Action Model with Episodic World Modeling for General Robot Control
Zhenyang Liu, Yongchong Gu, Sixiao Zheng +3
Recent advances in vision-language models (VLMs) have enabled robots to follow open-ended instructions and demonstrate impressive commonsense reasoning. However, current vision-lan…