Selective Agentic Recovery for UAV Autonomy with a Persistent Mission Runtime
Agentic AI can support unmanned aerial vehicle (UAV) autonomy by providing high-level recovery reasoning when local waypoint- or setpoint-based execution encounters blocked passages, repeated no-progress behavior, or mission-level ambiguity. On physical UAVs, however, remote reasoning is most useful when it is invoked selectively, since each call introduces latency, resource cost, backend uncertainty, and a need to validate the returned decision. This paper presents Persistent Mission Runtime (PMR), a UAV recovery framework that keeps the mission loop and safety-critical execution local while using an external agentic reasoner only as an on-demand recovery module. The reasoner selects fro...
| Authors | Taewoo Park, Kyeonghyun Yoo, Seunghyun Yoo et al. |
|---|---|
| Primary category | cs.RO |
| Published | 12 June 2026 |
| Last updated at source | 12 June 2026 |
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