The paper introduces Contextual Safety Filtering (CSF), a training‑free method that enforces natural‑language safety rules on text‑conditioned motion generators by comparing generated trajectories to safe and unsafe reference paths. CSF uses an affine safety value derived from these references and a safe reference tracking CBF‑QP to activate rules in both explicit and scene‑triggered unsafe scenarios. Experiments on four pretrained generators show CSF reduces danger‑event rates by up to 90% while preserving 88‑100% of benign motions, and a real‑world Unitree G1 robot demonstrates successful prevention of unsafe motions in diverse human and object interaction settings.
By Lizhi Yang, Yiling Hou, Yao Tang, Junheng Li, Daniel Weng, Blake Werner, Aaron D. Ames
arXiv:2608.21928v1 Announce Type: new
Abstract: In embodied AI, safety risk can be latent: a benign instruction and a safe scene become hazardous only when composed. Prior work has advanced embodied...
By Zhesheng Zhang, Jiahao Lu, Wei Liu, Cong Pan, Jianhua Yang, Yixiang Chen, Hongyuan Yu, Mengqi Zhang, Kailin Lyu, Zhumin Chen, Keji He
arXiv:2606. 05290v1 Announce Type: cross Abstract: Recent progress in generative modeling has made safety control a central challenge, yet existing approaches remain largely model-specific, requiring retraining or tailored interventions for each new architecture.
By Tobia Poppi, Silvia Cappelletti, Sara Sarto, Florian Schiffers, Garin Kessler, Marcella Cornia, Lorenzo Baraldi, Rita Cucchiara
arXiv:2607. 14543v1 Announce Type: cross Abstract: Vision-language models (VLMs) are increasingly used as the reasoning backbone of embodied agents, enabling robots to interpret visual scenes, follow language instructions, and plan multi-step actions.
By Huaigang Yang, Ya Li, Min Ren, Bo Dai, Zhenliang Zhang, Zhaofeng He
arXiv:2607. 00218v1 Announce Type: cross Abstract: Vision-language models (VLMs) are now proposed as runtime safety guards for embodied agents in homes and factories.
By Siddhant Panpatil, Arth Singh, Mijin Koo, Chaeyun Kim, Haon Park, Dasol Choi
arXiv:2607. 18325v1 Announce Type: cross Abstract: Modern safety-critical systems increasingly rely on human-robot interaction to reduce disaster risk and support decision-making during emergencies.
By Murali Indukuri, Mohammad Eskandari, Sree Nitya Kollu, Stephanie Lukin, Cynthia Matuszek