6 papers
What Foundation Models can Bring for Robot Learning in Manipulation : A Survey
Dingzhe Li, Yixiang Jin, Yuhao Sun +11
The realization of universal robots is an ultimate goal of researchers. However, a key hurdle in achieving this goal lies in the robots' ability to manipulate objects in their unst…
What Really Matters for Robust Multi-Sensor HD Map Construction?
Xiaoshuai Hao, Yuting Zhao, Yuheng Ji +5
High-definition (HD) map construction methods are crucial for providing precise and comprehensive static environmental information, which is essential for autonomous driving system…
VTLA: Vision-Tactile-Language-Action Model with Preference Learning for Insertion Manipulation
Chaofan Zhang, Peng Hao, Xiaoge Cao +3
While vision-language models have advanced significantly, their application in language-conditioned robotic manipulation is still underexplored, especially for contact-rich tasks t…
CLTP: Contrastive Language-Tactile Pre-training for 3D Contact Geometry Understanding
Wenxuan Ma, Xiaoge Cao, Yixiang Zhang +7
Recent advancements in integrating tactile sensing with vision-language models (VLMs) have demonstrated remarkable potential for robotic multimodal perception. However, existing ta…
TLA: Tactile-Language-Action Model for Contact-Rich Manipulation
Peng Hao, Chaofan Zhang, Dingzhe Li +4
Significant progress has been made in vision-language models. However, language-conditioned robotic manipulation for contact-rich tasks remains underexplored, particularly in terms…
MapFusion: A Novel BEV Feature Fusion Network for Multi-modal Map Construction
Xiaoshuai Hao, Yunfeng Diao, Mengchuan Wei +7
Map construction task plays a vital role in providing precise and comprehensive static environmental information essential for autonomous driving systems. Primary sensors include c…