10 papers
HOST:Robots Acquire Manipulation Skills in Seconds from a Single Human Video
Guangyan Chen, Meiling Wang, Te Cui +9
The ability to acquire skills rapidly and effortlessly while retaining those already mastered is essential for robots. However, current methods still rely on a cumbersome training-…
CubifyGS: Object-Centric 3D Gaussian Splatting for Lifelong Dynamic Scene Maintenance
Bohan Ren, Dianyi Yang, Shiyang Liu +5
Lifelong scene mapping under rigid object rearrangement remains a fundamental challenge in robotics. While 3D Gaussian Splatting (3DGS) enables high-fidelity modeling, primitive-le…
OmniMap: A General Mapping Framework Integrating Optics, Geometry, and Semantics
Yinan Deng, Yufeng Yue, Jianyu Dou +5
Robotic systems demand accurate and comprehensive 3D environment perception, requiring simultaneous capture of photo-realistic appearance (optical), precise layout shape (geometric…
FMimic: Foundation Models are Fine-grained Action Learners from Human Videos
Guangyan Chen, Meiling Wang, Te Cui +8
Visual imitation learning (VIL) provides an efficient and intuitive strategy for robotic systems to acquire novel skills. Recent advancements in foundation models, particularly Vis…
Automated 3D-GS Registration and Fusion via Skeleton Alignment and Gaussian-Adaptive Features
Shiyang Liu, Dianyi Yang, Yu Gao +3
In recent years, 3D Gaussian Splatting (3D-GS)-based scene representation demonstrates significant potential in real-time rendering and training efficiency. However, most existing…
MCOO-SLAM: A Multi-Camera Omnidirectional Object SLAM System
Miaoxin Pan, Jinnan Li, Yaowen Zhang +2
Object-level SLAM offers structured and semantically meaningful environment representations, making it more interpretable and suitable for high-level robotic tasks. However, most e…