Abstract
Embodied task planners may produce multi-step plans whose subtask dependencies and interactions with the environment create physical risks during execution. Yet existing safeguards overlook such compositional risks, as general-purpose guardrails focus on semantic harm and embodied safety detectors assess subtasks in isolation. To address this gap, we introduce PlanGuard, the first pre-execution detector that evaluates the physical safety of a complete multi-step plan in its current environment. For training and evaluation, we construct a Multi-Step Plan Safety (MSP-Safe) dataset through paired task construction, plan generation using diverse planners, and safety annotation by three judges. Task-oriented SFT on MSP-Safe establishes fundamental plan-safety assessment capabilities, yet a substantial gap remains between compact models suitable for real-time deployment and stronger but costlier large models. Accordingly, we propose Strong-Teacher Adaptive Compensation for On-Policy Distillation (STAC-OPD), which provides compact models with adaptive strong-teacher supervision along their on-policy trajectories. It combines token-level distribution transfer from a fine-tuned strong teacher with probability-routed sequence-level compensation, retaining student-generated targets when the student favors the reference safety decision and using teacher-reconstructed targets otherwise. Across all test subsets, PlanGuard-2B achieves average 87.15% ACC and 87.21% F1, demonstrating effective whole-plan physical-risk detection at compact model scale. Code and dataset will be publicly released.
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Cite this article
APA 7
Chen, J., Miao, C., Xiang, Y., Jin, Z., Yuan, H., Chu, Q., Gong, T., Liu, H., Zhang, B., Cai, J., Li, Z., & Yu, N. (2026). PlanGuard: A Guardrail for Multi-Step Plan Safety in Embodied Agents. https://omanscience.com/en/articles/planguard-a-guardrail-for-multi-step-plan-safety-in-embodied-agents
MLA 9
Chen, Junchi, et al. "PlanGuard: A Guardrail for Multi-Step Plan Safety in Embodied Agents." https://omanscience.com/en/articles/planguard-a-guardrail-for-multi-step-plan-safety-in-embodied-agents.
Chicago (author–date)
Chen, Junchi, Changtao Miao, Yuxiao Xiang, Zhenchao Jin, Haojie Yuan, Qi Chu, Tao Gong, He Liu, Bo Zhang, Jiansheng Cai, Zhe Li, and Nenghai Yu. 2026. "PlanGuard: A Guardrail for Multi-Step Plan Safety in Embodied Agents." https://omanscience.com/en/articles/planguard-a-guardrail-for-multi-step-plan-safety-in-embodied-agents.
Harvard
Chen, J., Miao, C., Xiang, Y., Jin, Z., Yuan, H., Chu, Q., Gong, T., Liu, H., Zhang, B., Cai, J., Li, Z. and Yu, N. (2026) 'PlanGuard: A Guardrail for Multi-Step Plan Safety in Embodied Agents', Available at: https://omanscience.com/en/articles/planguard-a-guardrail-for-multi-step-plan-safety-in-embodied-agents.
Vancouver
Chen J, Miao C, Xiang Y, Jin Z, Yuan H, Chu Q, et al. PlanGuard: A Guardrail for Multi-Step Plan Safety in Embodied Agents. https://omanscience.com/en/articles/planguard-a-guardrail-for-multi-step-plan-safety-in-embodied-agents
IEEE
J. Chen, C. Miao, Y. Xiang, Z. Jin, H. Yuan, Q. Chu, T. Gong, H. Liu, B. Zhang, J. Cai, Z. Li, and N. Yu, "PlanGuard: A Guardrail for Multi-Step Plan Safety in Embodied Agents," https://omanscience.com/en/articles/planguard-a-guardrail-for-multi-step-plan-safety-in-embodied-agents.