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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| Main Authors: | , , , |
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| Format: | Article |
| Language: | zho |
| Published: |
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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| Summary: | 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. |
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| ISSN: | 2096-5427 |