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.


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    Title :

    Research on Multi - Sensor Fusion Technology of IMU LiDAR and GNSS for Autonomous Driving


    Contributors:


    Publication date :

    2025-03-21


    Size :

    1356114 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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