Object Search in Partially-Known Environments via LLM-informed Model-based Planning and Prompt Selection
We present a novel LLM-informed model-based planning framework, and a novel prompt selection method, for object search in partially-known environments. Our approach uses an LLM to estimate statistics about the likelihood of finding the target object when searching various locations throughout the scene that, combined with travel costs extracted from the environment map, are used to instantiate a model, thus using the LLM to inform planning and achieve effective search performance. Moreover, the abstraction upon which our approach relies is amenable to deployment-time model selection via the recent offline replay approach, an insight we leverage to enable fast prompt and LLM selection duri...
| Authors | Abhishek Paudel, Abhish Khanal, Raihan I. Arnob et al. |
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| Primary category | cs.RO |
| Published | 25 March 2026 |
| Last updated at source | 7 July 2026 |
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