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arXiv AI By Xi Chen, Zhe Liu, Xiaogang Xu, Jiafei Xu, Chunyi Zhou, Yuan Su, Rui Zeng, Tianyu Du, Kelu Yao, Chao Li, Shouling Ji

Speaking the Navigator's Language: Trajectory-Grounded Instruction Translation for Frozen Aerial VLN Agents

Read the original on arXiv AI →

The paper introduces the Trajectory-Grounded Instruction Translator (TGIT), a front‑end that keeps an aerial vision‑and‑language navigation agent frozen while translating short, intent‑driven user instructions into executable commands. By prompting a language model with human‑written style examples, TGIT learns from the agent’s trajectory outcomes and improves success rates from 11.33 % to 37.93 % on weak inputs, and from 11.33 % to 32.51 % on real human instructions. The method also boosts performance on held‑out OpenFly data and provides recovery on CityNav and AirVLN benchmarks.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

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