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...

Celý popis

Uložené v:
Podrobná bibliografia
Vydané v:2025 5th International Conference on Sensors and Information Technology s. 407 - 410
Hlavný autor: Cheng, Zexiang
Médium: Konferenčný príspevok..
Jazyk:English
Vydavateľské údaje: IEEE 21.03.2025
Predmet:
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
On-line prístup:Získať plný text
Tagy: Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
Popis
Shrnutí: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.
DOI:10.1109/ICSI64877.2025.11009780