@inproceedings{39e213a4d5fe4f55ad3b1667f8aacf2e,
title = "Terrain Recognition for Unstructured Environments Using BiLSTM-Transformer Networks Under Multi-domain E/E Architecture",
abstract = "This paper introduces a novel terrain recognition method designed for unstructured environments, combining BiLSTM and Transformer encoder networks. The BiLSTM effectively captures temporal dependencies in the data, while the Transformer{\textquoteright}s attention mechanism models the correlations between control commands and trajectory information. The proposed method demonstrates an impressive accuracy of 0.9696 on the test set. Furthermore, a deployment strategy is outlined for integrating the method within the modern multi-domain electronic and electrical (E/E) architecture of unmanned ground vehicles, providing valuable insights for real-world applications.",
keywords = "Deep learning, E/E architecture, Terrain recognition, Unmanned ground vehicle",
author = "Jie Fan and Xudong Zhang and Yijie Chen and Jiangbo Geng and Yutong Jiang and Xuan Liu",
note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2026.; 3rd CCF Intelligent Vehicles Symposium, CIVS 2025 ; Conference date: 16-08-2025 Through 18-08-2025",
year = "2026",
doi = "10.1007/978-981-95-4875-0\_1",
language = "English",
isbn = "9789819548743",
series = "Communications in Computer and Information Science",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "1--12",
editor = "Huiyun Li and Zhongli Wang and Shuai Zhao and Peng Sun and Michael Herrmann and Xi Zheng and Yuling Liu",
booktitle = "Intelligent Vehicles - 3rd CCF Intelligent Vehicles Symposium, CIVS 2025, Revised Selected Papers",
address = "Germany",
}