As You Wish: Mission Planning with Formal Verification using LLMs in Precision Agriculture
Though robotic systems are now being commercialized and deployed in various industries, many of these systems are highly specialized and often require an advanced skill set to operate and ensure they perform as instructed. To mitigate this problem, we recently introduced a mission planner leveraging LLMs to synthesize mission plans in precision agriculture based on mission descriptions provided in natural language. While the system demonstrates impressive performance, it also suffers from the inherent ambiguities of natural language. In this paper, we extend our system to address this issue by introducing multiple feedback loops in the planning architecture that leverage linear temporal l...
| Authors | Marcos Abel Zuzuárregui, Stefano Carpin |
|---|---|
| Primary category | cs.RO |
| Published | 16 June 2026 |
| Last updated at source | 5 August 2026 |
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