@inproceedings{f48952750e4c45e99ac0843dcc196379,
title = "L2R-Nav: A Large Language Model-Enhanced Framework for Robotic Navigation",
abstract = "Robot navigation in dynamic, unfamiliar environments poses a significant challenge, as it traditionally relies on static maps, which are inadequate for the ever-changing scenarios encountered in daily life. This paper introduces L2R-Nav, an innovative, end-to-end intelligent robot navigation framework. It harnesses large language model technology combined with reinforcement learning to facilitate navigation tasks based on user instructions. L2R-Nav integrates the sophisticated cognitive abilities of large language models with the training of a local navigation model, employing a novel probabilistic graph approach. This integration is aimed at pioneering new methodologies in robot interaction and navigation. The robustness and effectiveness of the L2R-Nav framework are demonstrated through extensive empirical evaluations in a variety of environments, underscoring its potential as a significant advancement in the field of robotic navigation.",
keywords = "End-to-end Navigation, Probability Graph, Reinforcement Learning, Robot Interaction",
author = "Xiaoze Wu and Qingfeng Li and Chen Chen and Xinlei Zhang and Haochen Zhao and Jianwei Niu",
note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.; 17th International Conference on Knowledge Science, Engineering and Management, KSEM 2024 ; Conference date: 16-08-2024 Through 18-08-2024",
year = "2024",
doi = "10.1007/978-981-97-5501-1\_6",
language = "英语",
isbn = "9789819755004",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "73--84",
editor = "Cungeng Cao and Huajun Chen and Liang Zhao and Junaid Arshad and Yonghao Wang and Taufiq Asyhari",
booktitle = "Knowledge Science, Engineering and Management - 17th International Conference, KSEM 2024, Proceedings",
address = "德国",
}