Design of Dust-Filtering Algorithms for LiDAR Sensors Using Intensity and Range Information in Off-Road Vehicles
Although the LiDAR sensor provides high-resolution point cloud data, its performance degrades when exposed to dust environments, which may cause a failure in perception for robotics applications. To address this issue, our study designed an intensity-based filter that can remove dust particles from...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-05-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/22/11/4051 |
| _version_ | 1827663958944776192 |
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| author | Ali Afzalaghaeinaeini Jaho Seo Dongwook Lee Hanmin Lee |
| author_facet | Ali Afzalaghaeinaeini Jaho Seo Dongwook Lee Hanmin Lee |
| author_sort | Ali Afzalaghaeinaeini |
| collection | DOAJ |
| description | Although the LiDAR sensor provides high-resolution point cloud data, its performance degrades when exposed to dust environments, which may cause a failure in perception for robotics applications. To address this issue, our study designed an intensity-based filter that can remove dust particles from LiDAR data in two steps. In the first step, it identifies potential points that are likely to be dust by using intensity information. The second step involves analyzing the point density around selected points and removing them if they do not meet the threshold criterion. To test the proposed filter, we collected experimental data sets under the existence of dust and manually labeled them. Using these data, the de-dusting performance of the designed filter was evaluated and compared to several types of conventional filters. The proposed filter outperforms the conventional ones in achieving the best performance with the highest <i>F1</i> score and removing dust without sacrificing the original surrounding data. |
| first_indexed | 2024-03-10T00:52:35Z |
| format | Article |
| id | doaj.art-25cdd3b58d9746eba9a9da8fc9f905a8 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T00:52:35Z |
| publishDate | 2022-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-25cdd3b58d9746eba9a9da8fc9f905a82023-11-23T14:47:54ZengMDPI AGSensors1424-82202022-05-012211405110.3390/s22114051Design of Dust-Filtering Algorithms for LiDAR Sensors Using Intensity and Range Information in Off-Road VehiclesAli Afzalaghaeinaeini0Jaho Seo1Dongwook Lee2Hanmin Lee3Department of Automotive and Mechatronics Engineering, Ontario Tech University, Oshawa, ON L1G 0C5, CanadaDepartment of Automotive and Mechatronics Engineering, Ontario Tech University, Oshawa, ON L1G 0C5, CanadaDepartment of Smart Industrial Machine Technologies, Korean Institute of Machinery & Materials, Daejeon 34103, KoreaDepartment of Smart Industrial Machine Technologies, Korean Institute of Machinery & Materials, Daejeon 34103, KoreaAlthough the LiDAR sensor provides high-resolution point cloud data, its performance degrades when exposed to dust environments, which may cause a failure in perception for robotics applications. To address this issue, our study designed an intensity-based filter that can remove dust particles from LiDAR data in two steps. In the first step, it identifies potential points that are likely to be dust by using intensity information. The second step involves analyzing the point density around selected points and removing them if they do not meet the threshold criterion. To test the proposed filter, we collected experimental data sets under the existence of dust and manually labeled them. Using these data, the de-dusting performance of the designed filter was evaluated and compared to several types of conventional filters. The proposed filter outperforms the conventional ones in achieving the best performance with the highest <i>F1</i> score and removing dust without sacrificing the original surrounding data.https://www.mdpi.com/1424-8220/22/11/4051LiDARfilteringalgorithmLIORLIDRORde-dusting |
| spellingShingle | Ali Afzalaghaeinaeini Jaho Seo Dongwook Lee Hanmin Lee Design of Dust-Filtering Algorithms for LiDAR Sensors Using Intensity and Range Information in Off-Road Vehicles Sensors LiDAR filtering algorithm LIOR LIDROR de-dusting |
| title | Design of Dust-Filtering Algorithms for LiDAR Sensors Using Intensity and Range Information in Off-Road Vehicles |
| title_full | Design of Dust-Filtering Algorithms for LiDAR Sensors Using Intensity and Range Information in Off-Road Vehicles |
| title_fullStr | Design of Dust-Filtering Algorithms for LiDAR Sensors Using Intensity and Range Information in Off-Road Vehicles |
| title_full_unstemmed | Design of Dust-Filtering Algorithms for LiDAR Sensors Using Intensity and Range Information in Off-Road Vehicles |
| title_short | Design of Dust-Filtering Algorithms for LiDAR Sensors Using Intensity and Range Information in Off-Road Vehicles |
| title_sort | design of dust filtering algorithms for lidar sensors using intensity and range information in off road vehicles |
| topic | LiDAR filtering algorithm LIOR LIDROR de-dusting |
| url | https://www.mdpi.com/1424-8220/22/11/4051 |
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