Embodied agents learn to handle task interruptions and resume navigation
Preemptive Instruction Following with Resumption
Robotics
Summary
Sometimes robots or agents navigating a space get new orders before finishing their current task. This paper by the authors introduces a test called PIFR to see how well agents can pause their current task, do the new one, and then continue where they left off. They found agents work better in some interruption types than others, and simple methods can help them get back on track. This helps computers that move around follow instructions even when those instructions change suddenly.
What this means in practice
- •For robotics engineers: Improve robots’ ability to handle changing navigation commands mid-task and resume original goals accurately in dynamic environments.
- •For drone navigation teams: Enhance drone systems to interrupt current missions, execute priority tasks, and resume original routes effectively after environmental changes.
Authors
Zerun Liu, Lechao Cheng, Yimin Liu, Shengeng Tang, Yaxiong Wang, Zhun Zhong
Abstract
Long-horizon embodied navigation may be interrupted by a higher-priority instruction before the current task sequence is complete. The agent must finish its current atomic task, execute the inserted task, and resume the remaining sequence from the updated environment state, where its viewpoint and available navigation candidates may have changed. To evaluate this capability, we introduce PIFR benchmark, a novel task for runtime task preemption and resumption in embodied navigation. PIFR includes single, repeated, and nested interruption settings,with stage-specific metrics for inserted-task completion, resumption of the original task, and completion of the full sequence. Evaluations show that recovery performance varies across interruption conditions, while aggregate success can obscure differences in interruption handling and resumption. We further propose a lightweight candidate-ranking baseline to improve target re-grounding after interruption. Together, PIFR and the baseline provide a systematic framework for studying interruption handling and task recovery in long-horizon embodied navigation.