IROS

OmniV2X: A Generative Foundation Planner for Efficient End-to-End Cooperative Driving

OmniV2X：一种用于高效端到端协同驾驶的生成式基础规划器

Juntong Peng, Juanwu Lu, Yupeng Zhou, Can Cui, Yaobin Chen, Ziran Wang

机构 * Purdue University（普渡大学） 纠错

AI总结 提出OmniV2X生成式基础模型，通过端到端监督训练和交叉注意力注入，利用多模态多智能体上下文实现高效协同驾驶，在DAIR-V2X-Seq数据集上以少于10%微调数据和1%通信带宽达到最优性能。

Comments Accepted to IROS 2026

AnyCamVLA: Zero-Shot Camera Adaptation for Viewpoint Robust Vision-Language-Action Models

AnyCamVLA: 零样本相机适应用于视角鲁棒的视觉-语言-动作模型

Hyeongjun Heo, Seungyeon Woo, Sang Min Kim, Junho Kim, Junho Lee, Yonghyeon Lee, Young Min Kim

机构 * Department of Electrical and Computer Engineering, Seoul National University（电子与计算机工程系，首尔国立大学） ； Department of Mechanical Engineering, Massachusetts Institute of Technology（机械工程系，麻省理工学院） 纠错

AI总结 AnyCamVLA通过零样本相机适应提升视觉-语言-动作模型在视角变化下的鲁棒性，适用于任何RGB策略。

Comments Accepted to IROS 2026