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A Real-Time Road Boundary Detection Approach in Surface Mine Based on Meta Random Forest | |
Ai, Yunfeng1,2; Song, Ruiqi2,3,4; Huang, Chongqing1,2; Cui, Chenglin1,2; Tian, Bin2,3![]() ![]() | |
发表期刊 | IEEE TRANSACTIONS ON INTELLIGENT VEHICLES
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ISSN | 2379-8858 |
2024 | |
卷号 | 9期号:1页码:1989-2001 |
摘要 | Efficient and accurate road boundary detection is a fundamental building component of the perception system for autonomous driving. Specially, the challenges for road boundary detection in surface mine are high generalization error of model and difficulty in boundary generation, which caused by diversity of samples along with scarcity for corresponding samples and complexity of terrain respectively. Therefore, a novel road boundary detection framework, which execute in a high efficiency way with considerable performance, is proposed for the problems mentioned above. Firstly, point cloud pre-processing methods, including point cloud down-sampling, filtering and clustering, are conducted for achieving clusters of objects in surface mine. Then, a meta random forest classification method, which combines meta learning and random forest for enhancing the generalization ability of the model and overcoming sample scarcity of surface mine, is proposed for classifying point cloud clusters of retaining wall on both side of the road. At last, the boundary of unstructured road is generated by conducting a series of post-processing methods corresponds to the unevenness and irregularity of unstructured road. Experiments are carried out on the collected and labeled datasets of surface mine. The results illustrate that our proposed method can effectively detect road boundary of surface mine in real-time with considerable performance. |
关键词 | Roads Point cloud compression Laser radar Random forests Metalearning Surface treatment Feature extraction Road boundary detection Point Cloud meta learning random forest few shot classification autonomous driving |
DOI | 10.1109/TIV.2023.3296767 |
关键词[WOS] | INTELLIGENT VEHICLES ; EDGE-DETECTION ; TRACKING |
收录类别 | SCI |
语种 | 英语 |
资助项目 | National Key R&D Program of China[2022YFB4703700] ; Key-Area Research and Development Program of Guangdong Province[2020B0909050001] ; Key-Area Research and Development Program of Guangdong Province[2020B090921003] ; Natural Science Foundation of Shannxi Province[2020JM-195] ; Natural Science Foundation of Hebei Province[2021402011] ; National Key Research and Development Project[B019030051] ; National Natural Science Foundation of China[61503380] ; National Natural Science Foundation of China[61773381] ; National Natural Science Foundation of China[U1811463] |
项目资助者 | National Key R&D Program of China ; Key-Area Research and Development Program of Guangdong Province ; Natural Science Foundation of Shannxi Province ; Natural Science Foundation of Hebei Province ; National Key Research and Development Project ; National Natural Science Foundation of China |
WOS研究方向 | Computer Science ; Engineering ; Transportation |
WOS类目 | Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic ; Transportation Science & Technology |
WOS记录号 | WOS:001173317800169 |
出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
七大方向——子方向分类 | 其他 |
国重实验室规划方向分类 | 其他 |
是否有论文关联数据集需要存交 | 否 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/58734 |
专题 | 多模态人工智能系统全国重点实验室_平行智能技术与系统团队 |
通讯作者 | Song, Ruiqi |
作者单位 | 1.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China 2.Waytous Inc, Qingdao 266109, Peoples R China 3.Chinese Acad Sci, Inst Automat, State Key Lab Multimodal Artificial Intelligence, Beijing 100190, Peoples R China 4.Tongji Univ, Coll Surveying & Geo Informat, Shanghai 200092, Peoples R China |
通讯作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Ai, Yunfeng,Song, Ruiqi,Huang, Chongqing,et al. A Real-Time Road Boundary Detection Approach in Surface Mine Based on Meta Random Forest[J]. IEEE TRANSACTIONS ON INTELLIGENT VEHICLES,2024,9(1):1989-2001. |
APA | Ai, Yunfeng,Song, Ruiqi,Huang, Chongqing,Cui, Chenglin,Tian, Bin,&Chen, Long.(2024).A Real-Time Road Boundary Detection Approach in Surface Mine Based on Meta Random Forest.IEEE TRANSACTIONS ON INTELLIGENT VEHICLES,9(1),1989-2001. |
MLA | Ai, Yunfeng,et al."A Real-Time Road Boundary Detection Approach in Surface Mine Based on Meta Random Forest".IEEE TRANSACTIONS ON INTELLIGENT VEHICLES 9.1(2024):1989-2001. |
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