arXiv · 2610.14038
From bits to atoms: A survey of cross-layer safety in Embodied AI
Abstract
Embodied Artificial Intelligence (AI) introduces cyber-physical risks because digital failures and attacks can cause physical harm. This survey organizes embodied AI safety through a four-layer reference architecture -- comprising the physical interaction, system and middleware, algorithm and decision, and cloud-edge and data layers -- and uses it to connect vulnerabilities, propagation paths, and safeguards across the system stack. It traces the evolution of safety paradigms and examines how faults and attacks cross architectural boundaries to produce physical consequences. Furthermore, the survey systematizes composite attack chains, outlines multi-layered defense strategies, and reviews representative embodied safety benchmarks. Ultimately, we advocate for unifying software alignment with rigorous hardware constraints to build trustworthy systems capable of operating safely within human-centric environments.
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Tuo Feng, Yue Zhang, Shiji Zhou, Zhaoxin Fan, Wenguan Wang, Xiaowei Chi, Tianyu Shen, Xiangtai Li, Xuesong Bai, Zheng Zhu, Sirui Han, Boyu Zhou, Zhaosong Wang, Shizhe Chen, Zilong Zheng, Chenjia Bai, Jiangmiao Pang, Yaodong Yang, Hao Zhao, Di Hu, Li Yi, Yan Huang, Qi Wu, Hanwang Zhang, Fei Gao, Shanghang Zhang, Hongsheng Li, Jianye Hao, Yuan Zhang, Yingjie Xia, Jian Shen, Cewu Lu, Hui Zhang, Kai Chen, Wenwu Yu, Badong Chen, Jungong Han, Yike Guo. 2026-10-02. From bits to atoms: A survey of cross-layer safety in Embodied AI. https://doi.org/10.59717/ipj.aiplus.2026.100013
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