11 papers
VER: Vision Expert Transformer for Robot Learning via Foundation Distillation and Dynamic Routing
Yixiao Wang, Mingxiao Huo, Zhixuan Liang +8
Pretrained vision foundation models (VFMs) advance robotic learning via rich visual representations, yet individual VFMs typically excel only in specific domains, limiting generali…
Accelerating Transformer-Based Monocular SLAM via Geometric Utility Scoring
Xinmiao Xiong, Bangya Liu, Hao Wang +7
Geometric Foundation Models (GFMs) have recently advanced monocular SLAM by providing robust, calibration-free 3D priors. However, deploying these models on dense video streams int…
DexH2R: Task-oriented Dexterous Manipulation from Human to Robots
Shuqi Zhao, Xinghao Zhu, Yuxin Chen +5
Dexterous manipulation is a critical aspect of human capability, enabling interaction with a wide variety of objects. Recent advancements in learning from human demonstrations and…
Interleave-VLA: Enhancing Robot Manipulation with Interleaved Image-Text Instructions
Cunxin Fan, Xiaosong Jia, Yihang Sun +8
The rise of foundation models paves the way for generalist robot policies in the physical world. Existing methods relying on text-only instructions often struggle to generalize to…
P2 Explore: Efficient Exploration in Unknown Cluttered Environment with Floor Plan Prediction
Kun Song, Gaoming Chen, Masayoshi Tomizuka +3
Robot exploration aims at the reconstruction of unknown environments, and it is important to achieve it with shorter paths. Traditional methods focus on optimizing the visiting ord…
Towards Interactive and Learnable Cooperative Driving Automation: a Large Language Model-Driven Decision-Making Framework
Shiyu Fang, Jiaqi Liu, Mingyu Ding +4
At present, Connected Autonomous Vehicles (CAVs) have begun to open road testing around the world, but their safety and efficiency performance in complex scenarios is still not sat…