LEARNING
GASE：基于高斯泼溅的具身仿真环境重建自动化系统
Jiawei Zhang, Yiming Yan, Chao Liang, Nuo Xu, Seson Sun, Qichen Zhang, Yuhao Xu, Yantai Yang, Yingqiao Wang, Qin Jin, Zhipeng Zhang
- 发表年份
- 2026
- 访问权限
- 开放获取
摘要
本文提出GASE系统，利用全景相机阵列的多视角视频流实现快速环境扫描，并通过相机位姿策略鲁棒提取前景物体并修复背景。该系统能独立重建前景与静态背景并导入物理仿真器，在分割精度上比现有3D高斯方法提升超过10%。
关键词
scene reconstructionsim-to-real3D Gaussian splattingembodied AIautomated pipeline
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