Research on Multi - Sensor Fusion Technology of IMU LiDAR and GNSS for Autonomous Driving
With the remarkable development of the practicality of deep learning and the ultra - high - speed information transmission rate of 5G communication technology, autonomous driving is becoming a key technology that affects future industries. Sensors are crucial for perceiving the external world in aut...
Uloženo v:
| Vydáno v: | 2025 5th International Conference on Sensors and Information Technology s. 407 - 410 |
|---|---|
| Hlavní autor: | |
| Médium: | Konferenční příspěvek |
| Jazyk: | angličtina |
| Vydáno: |
IEEE
21.03.2025
|
| Témata: | |
| On-line přístup: | Získat plný text |
| Tagy: |
Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
|
| Abstract | With the remarkable development of the practicality of deep learning and the ultra - high - speed information transmission rate of 5G communication technology, autonomous driving is becoming a key technology that affects future industries. Sensors are crucial for perceiving the external world in autonomous driving systems, and their performance influences the safety of autonomous vehicles. In this study, we deeply explore the multi - sensor fusion technology of IMU, LiDAR and GNSS for autonomous driving. A fusion architecture and algorithm are designed based on the Extended Kalman Filter. The predicted position state curve of the vehicle after incorporating the machine learning model is discussed. It is concluded that the sensor fusion technology after integrating the Random Forest model algorithm can more precisely predict the position state of the vehicle. |
|---|---|
| AbstractList | With the remarkable development of the practicality of deep learning and the ultra - high - speed information transmission rate of 5G communication technology, autonomous driving is becoming a key technology that affects future industries. Sensors are crucial for perceiving the external world in autonomous driving systems, and their performance influences the safety of autonomous vehicles. In this study, we deeply explore the multi - sensor fusion technology of IMU, LiDAR and GNSS for autonomous driving. A fusion architecture and algorithm are designed based on the Extended Kalman Filter. The predicted position state curve of the vehicle after incorporating the machine learning model is discussed. It is concluded that the sensor fusion technology after integrating the Random Forest model algorithm can more precisely predict the position state of the vehicle. |
| Author | Cheng, Zexiang |
| Author_xml | – sequence: 1 givenname: Zexiang surname: Cheng fullname: Cheng, Zexiang email: 22062018@hdu.edu.cn organization: Hangzhou Dianzi University,Hangzhou,China |
| BookMark | eNo1j11LwzAYRiPohc79A8H8gc42aZrksnRuFjaFtV54NfLxZgt0ifRD2L93ol4dOBweeO7QdYgBEHrM0kWWpfKprpq6yAXnC5IS9uNSyUV6heaSS0FpxnIiBL9FHzsYQPXmiGPA26kbPU5wA2GIPV5Ng7_YFswxxC4ezjg6XG_f8cYvyx1WweL1a9Ngd2nLaYwhnuI04GXvv3w43KMbp7oB5n-coXb13FYvyeZtXVflJvGSjgnThoDlxmqnCHCrADSHnOVZQYwm3BXUEVvYXElbUCEUpZZpS41hWlit6Aw9_M56ANh_9v6k-vP-_zD9Bg5oUOc |
| ContentType | Conference Proceeding |
| DBID | 6IE 6IL CBEJK RIE RIL |
| DOI | 10.1109/ICSI64877.2025.11009780 |
| DatabaseName | IEEE Electronic Library (IEL) Conference Proceedings IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume IEEE Xplore All Conference Proceedings IEEE Electronic Library (IEL) IEEE Proceedings Order Plans (POP All) 1998-Present |
| DatabaseTitleList | |
| Database_xml | – sequence: 1 dbid: RIE name: IEEE Electronic Library (IEL) url: https://ieeexplore.ieee.org/ sourceTypes: Publisher |
| DeliveryMethod | fulltext_linktorsrc |
| EISBN | 9798331542887 |
| EndPage | 410 |
| ExternalDocumentID | 11009780 |
| Genre | orig-research |
| GroupedDBID | 6IE 6IL CBEJK RIE RIL |
| ID | FETCH-LOGICAL-i93t-5bc2ed7cdbfa2e7daeeb7e454162cb27f63f2d6d4a9d6388a33d5bd3cc5b8dba3 |
| IEDL.DBID | RIE |
| IngestDate | Wed Jun 04 06:02:11 EDT 2025 |
| IsPeerReviewed | false |
| IsScholarly | false |
| Language | English |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-i93t-5bc2ed7cdbfa2e7daeeb7e454162cb27f63f2d6d4a9d6388a33d5bd3cc5b8dba3 |
| PageCount | 4 |
| ParticipantIDs | ieee_primary_11009780 |
| PublicationCentury | 2000 |
| PublicationDate | 2025-March-21 |
| PublicationDateYYYYMMDD | 2025-03-21 |
| PublicationDate_xml | – month: 03 year: 2025 text: 2025-March-21 day: 21 |
| PublicationDecade | 2020 |
| PublicationTitle | 2025 5th International Conference on Sensors and Information Technology |
| PublicationTitleAbbrev | ICSI |
| PublicationYear | 2025 |
| Publisher | IEEE |
| Publisher_xml | – name: IEEE |
| Score | 1.9027404 |
| Snippet | With the remarkable development of the practicality of deep learning and the ultra - high - speed information transmission rate of 5G communication technology,... |
| SourceID | ieee |
| SourceType | Publisher |
| StartPage | 407 |
| SubjectTerms | Adaptation models Autonomous vehicles Global navigation satellite system Laser radar Machine learning algorithms Machine learning models Multi - sensor fusion algorithms Predictive models Random forests Sensor fusion Sensor systems Sensors |
| Title | Research on Multi - Sensor Fusion Technology of IMU LiDAR and GNSS for Autonomous Driving |
| URI | https://ieeexplore.ieee.org/document/11009780 |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV07T8MwELZoxcAEiCLeuoE1bWMndjJWLYVKUFWkSGWq_DhLWRIUEn4_dtpSMTCwWdZJls4638P3fUfIvScYwoS6109KHkRC8yBJQwxMqpxZxgZ1qNphE2I-T1ardLEFq7dYGERsm8-w75ftX74pdeNLZQNPb-YZczqkIwTfgLW2PVvhMB3MxtmMuwBcuLSPxv2d9K-5Ka3bmB7_88AT0tsD8GDx41pOyQEWZ-R91yUHZQEtcBYCyFwaWlYwbXzVC_aFcigtzF7e4DmfjF5BFgYe51kGLkSFUVN7JINL-WFS5b6g0CPL6cNy_BRsJyMEecrqIFaaohHaKCspCiMRlcAodsEV1YoKy5mlhptIpsbZVyIZM7EyTOtYJUZJdk66RVngBQGFwwgtS5lUNmLcKu4EIk5RS5oYqS5Jz6tl_bHhvljvNHL1x_41OfLK911aNLwh3bpq8JYc6q86_6zu2hv7Br77mi4 |
| linkProvider | IEEE |
| linkToHtml | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1LSwMxEA5aBT2pWPHtHLxuH0n2dSyttYvtUtwK9VTymIW97Mq66-832bYWDx68hTAQmCGZR-b7hpBHSzCEATWvnxCew33lOUHYR0eH0lxLV6Pqy2bYhB_HwXIZzjdg9QYLg4hN8xl27LL5y9eFqm2prGvpzSxjzj45cDmnvTVca9O11e-F3WiYRJ4JwX2T-FG3s5X_NTmlcRzjk38eeUraOwgezH-cyxnZw_ycvG_75KDIoYHOggOJSUSLEsa1rXvBrlQORQrR7A2m2WjwCiLX8BwnCZggFQZ1ZbEMJumHUZnZkkKbLMZPi-HE2cxGcLKQVY4rFUXtKy1TQdHXAlH6yF0TXlElqZ96LKXa01yE2tywQDCmXamZUq4MtBTsgrTyIsdLAhJ7HFMWMiFTzrxUekaAexSVoIEW8oq0rVpWH2v2i9VWI9d_7D-Qo8liNl1No_jlhhxbQ9ieLdq_Ja2qrPGOHKqvKvss7xvrfQPxkZ11 |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Abook&rft.genre=proceeding&rft.title=2025+5th+International+Conference+on+Sensors+and+Information+Technology&rft.atitle=Research+on+Multi+-+Sensor+Fusion+Technology+of+IMU+LiDAR+and+GNSS+for+Autonomous+Driving&rft.au=Cheng%2C+Zexiang&rft.date=2025-03-21&rft.pub=IEEE&rft.spage=407&rft.epage=410&rft_id=info:doi/10.1109%2FICSI64877.2025.11009780&rft.externalDocID=11009780 |