具身智能采用鸟瞰图以实现可扩展机器人数据

报道来源 [4]

1. 量子位 (QbitAI) TIER_1 中文(ZH) · 量子位的朋友们 · 2026-06-12 04:11

   BEV Enters Embodied Intelligence: Cross-Dimensional Bringing Robot Data onto the Scaling Fast Lane

2. arXiv cs.AI TIER_1 English(EN) · Xin Zhou, Cong Miao · 2026-06-12 04:00

   EWAM: An Enhanced World Action Model for Closed-Loop Online Adaptation in Embodied Intelligence

   arXiv:2606.12690v1 Announce Type: cross Abstract: In this paper, we propose the Enhanced World Action Model (EWAM), a closed-loop online adaptation architecture built upon a pretrained and fully frozen Cosmos3 backbone network. Evaluated entirely under a zero-shot task protocol, …

3. arXiv cs.AI TIER_1 English(EN) · Yifu Yuan, Yaoting Huang, Xianze Yao, Yutong Li, Shuoheng Zhang, Linqi Han, Pengyi Li, Jiangeng Sun, Wenting Jia, Zhao Zhang, Yuhao Liu, Ruihao Liao, Yucheng Hu, Qiyu Wu, Yuxiao Li, Zibin Dong, Fei Ni, Yan Zheng, Shuyang Gu, Yi Ma, Hongyao Tang, Han Hu, … · 2026-06-11 04:00

   Embodied-R1.5: Evolving Physical Intelligence via Embodied Foundation Models

   arXiv:2606.11324v1 Announce Type: cross Abstract: We introduce Embodied-R1.5, a unified Embodied Foundation Model (EFM) that integrates comprehensive embodied reasoning capabilities, spanning embodied cognition, task planning, correction, and pointing, within a single architectur…

4. Hugging Face Daily Papers TIER_1 English(EN) · 2026-06-09 00:00

   Embodied-R1.5: Evolving Physical Intelligence via Embodied Foundation Models

   Embodied-R1.5 is a unified embodied foundation model that integrates embodied reasoning capabilities and achieves state-of-the-art performance on embodied vision-language benchmarks through a multi-task balanced reinforcement learning approach.