Map2Route: Benchmarking Compositional Language-Grounded Route Planning over Semantic Maps

Abstract:We introduce Map2Route, a human-curated benchmark for compositional language-grounded route planning over pre-built semantic maps. Map2Route contains 1,000 episodes across 40 scenes, where instructions use relational, comparative, and nested descriptions to identify route-relevant objects and regions, while specifying ordered must-pass regions, must-avoid requirements, five categories of soft preferences, and spatial and route-stage scopes, which is partially tested by existing works. Alongside Map2Route, we propose Grounding2Route, which combines executable code-as-grounding with verification-guided repair and scope-aware this http URL seven representative adapted baselines, Grounding2Route substantially outperforms existing methods in all metrics. Despite these gains, a substantial gap to human demonstrations remains, highlighting the difficulty of Map2Route and the considerable headroom for future progress. Additional qualitative results and resources are available on this https URL.

Robotics (cs.RO)

arXiv:2609.17910 [cs.RO]

(or arXiv:2609.17910v1 [cs.RO] for this version)

https://doi.org/10.48550/arXiv.2609.17910 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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