Small-scale intersection scan model for UGV in urban environment

Yi Yang, Li Hao, Hao Zhu, Lyu Ningyi, Song Wenjie

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

Intersection detection is a critical capacity for an Unmanned Ground Vehicle (UGV) to drive safely in structured urban environment. Large-scale intersections stamped on maps have plenty of features for detection while some unmapped small-scale urban intersections are hard to be identified. In this paper, we propose a novel intersection detection method conducted on the basis of Hidden Markov Model (HMM). This method is based on the intersection scan model to obtain the traversable directions to classify the intersection. The scan model is effective in dealing with both LIDAR and visual data. Combination of the scan model and the HMM can accurately estimate the traversable directions in consideration of both real-time and historic data. Results from simulations and real-world experiments have shown the functionality of the presented approach.

源语言英语
主期刊名2017 American Control Conference, ACC 2017
出版商Institute of Electrical and Electronics Engineers Inc.
4229-4235
页数7
ISBN(电子版)9781509059928
DOI
出版状态已出版 - 29 6月 2017
活动2017 American Control Conference, ACC 2017 - Seattle, 美国
期限: 24 5月 201726 5月 2017

出版系列

姓名Proceedings of the American Control Conference
ISSN(印刷版)0743-1619

会议

会议2017 American Control Conference, ACC 2017
国家/地区美国
Seattle
时期24/05/1726/05/17

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引用此

Yang, Y., Hao, L., Zhu, H., Ningyi, L., & Wenjie, S. (2017). Small-scale intersection scan model for UGV in urban environment. 在 2017 American Control Conference, ACC 2017 (页码 4229-4235). 文章 7963605 (Proceedings of the American Control Conference). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.23919/ACC.2017.7963605