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• W2890347893 abstract "We propose an end-to-end deep learning model for translating free-form natural language instructions to a high-level plan for behavioral robot navigation. We use attention models to connect information from both the user instructions and a topological representation of the environment. We evaluate our model's performance on a new dataset containing 10,050 pairs of navigation instructions. Our model significantly outperforms baseline approaches. Furthermore, our results suggest that it is possible to leverage the environment map as a relevant knowledge base to facilitate the translation of free-form navigational instruction." @default.
• W2890347893 created "2018-09-27" @default.
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• W2890347893 date "2018-09-24" @default.
• W2890347893 modified "2023-10-14" @default.
• W2890347893 title "Translating Navigation Instructions in Natural Language to a High-Level Plan for Behavioral Robot Navigation" @default.
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• W2890347893 doi "https://doi.org/10.48550/arxiv.1810.00663" @default.
• W2890347893 hasPublicationYear "2018" @default.
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