Locomotive Passable Area Detection Based on Onboard LiDAR
Passable area detection is one of the important parts for autonomous driving. An algorithm for real-time LiDAR(light detection and ranging) based locomotive passable area detection is proposed to extract the passable area in front of the locomotive. Firstly, the algorithm preprocesses the three-dime...
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| Format: | Article |
| Language: | zho |
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Editorial Office of Control and Information Technology
2021-01-01
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| Series: | Kongzhi Yu Xinxi Jishu |
| Subjects: | |
| Online Access: | http://ctet.csrzic.com/thesisDetails#10.13889/j.issn.2096-5427.2021.04.300 |
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| author | LIU Bangfan ZHANG Huiyuan LI Chen ZENG Xiang |
| author_facet | LIU Bangfan ZHANG Huiyuan LI Chen ZENG Xiang |
| author_sort | LIU Bangfan |
| collection | DOAJ |
| description | Passable area detection is one of the important parts for autonomous driving. An algorithm for real-time LiDAR(light detection and ranging) based locomotive passable area detection is proposed to extract the passable area in front of the locomotive. Firstly, the algorithm preprocesses the three-dimensional point cloud data collected by onboard LiDAR in order to improve the quality of point cloud. Secondly, point cloud data of rail will be detected via a region search algorithm and rail curves will be fitted by random sampling consensus algorithm. Then, the algorithm will find the current rail of the locomotive with a matching rule to decide its forward area. After that, the support vector data description algorithm will be used to detect transmission line towers which determine the warning area of the locomotive. Finally, the passable area of the locomotive is actually the combination of its forward area and warning area. Experimental results show that the average detection time of the detection algorithm is 56 ms, which meet the real-time requirement and has good robustness, thus providing support for the active anti-collision technology of locomotive autonomous driving. |
| format | Article |
| id | doaj-art-d77c5a0c4e5e4742853a110f3345f9cb |
| institution | Kabale University |
| issn | 2096-5427 |
| language | zho |
| publishDate | 2021-01-01 |
| publisher | Editorial Office of Control and Information Technology |
| record_format | Article |
| series | Kongzhi Yu Xinxi Jishu |
| spelling | doaj-art-d77c5a0c4e5e4742853a110f3345f9cb2025-08-25T06:50:05ZzhoEditorial Office of Control and Information TechnologyKongzhi Yu Xinxi Jishu2096-54272021-01-0138788282312113Locomotive Passable Area Detection Based on Onboard LiDARLIU BangfanZHANG HuiyuanLI ChenZENG XiangPassable area detection is one of the important parts for autonomous driving. An algorithm for real-time LiDAR(light detection and ranging) based locomotive passable area detection is proposed to extract the passable area in front of the locomotive. Firstly, the algorithm preprocesses the three-dimensional point cloud data collected by onboard LiDAR in order to improve the quality of point cloud. Secondly, point cloud data of rail will be detected via a region search algorithm and rail curves will be fitted by random sampling consensus algorithm. Then, the algorithm will find the current rail of the locomotive with a matching rule to decide its forward area. After that, the support vector data description algorithm will be used to detect transmission line towers which determine the warning area of the locomotive. Finally, the passable area of the locomotive is actually the combination of its forward area and warning area. Experimental results show that the average detection time of the detection algorithm is 56 ms, which meet the real-time requirement and has good robustness, thus providing support for the active anti-collision technology of locomotive autonomous driving.http://ctet.csrzic.com/thesisDetails#10.13889/j.issn.2096-5427.2021.04.300LiDAR3D point cloudrail detectionRANSAC (random sample consensus)SVDD(support vector data description)passable area |
| spellingShingle | LIU Bangfan ZHANG Huiyuan LI Chen ZENG Xiang Locomotive Passable Area Detection Based on Onboard LiDAR Kongzhi Yu Xinxi Jishu LiDAR 3D point cloud rail detection RANSAC (random sample consensus) SVDD(support vector data description) passable area |
| title | Locomotive Passable Area Detection Based on Onboard LiDAR |
| title_full | Locomotive Passable Area Detection Based on Onboard LiDAR |
| title_fullStr | Locomotive Passable Area Detection Based on Onboard LiDAR |
| title_full_unstemmed | Locomotive Passable Area Detection Based on Onboard LiDAR |
| title_short | Locomotive Passable Area Detection Based on Onboard LiDAR |
| title_sort | locomotive passable area detection based on onboard lidar |
| topic | LiDAR 3D point cloud rail detection RANSAC (random sample consensus) SVDD(support vector data description) passable area |
| url | http://ctet.csrzic.com/thesisDetails#10.13889/j.issn.2096-5427.2021.04.300 |
| work_keys_str_mv | AT liubangfan locomotivepassableareadetectionbasedononboardlidar AT zhanghuiyuan locomotivepassableareadetectionbasedononboardlidar AT lichen locomotivepassableareadetectionbasedononboardlidar AT zengxiang locomotivepassableareadetectionbasedononboardlidar |