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Driving Assistance System Based on Data Fusion of Multisource Sensors for Autonomous Unmanned Ground Vehicles by Yang, Jiachen (author);Liu, Shan (author);Su, Hansong (author);Tian, Ying (author) is a Computer Science article available to read on EtoBox.
What is Driving Assistance System Based on Data Fusion of Multisource Sensors for Autonomous Unmanned Ground Vehicles about?
Autonomous unmanned ground vehicle is a product of technological development. At present, it has become a trend to provide multi-view real-time environmental state for autonomous unmanned ground vehicles. And more and more object detection algorithms will be applied in autonomous driving. In the recent years, multi-sensor-based driving assistance systems have become a way to solve these problems. In this paper, we introduce a driving assistance system based on data fusion of multiple sensors for autonomous driving. On the one hand, six fisheye cameras and twelve ultrasonic radars are used to collect surround-view environmental state. On the other hand, this system uses a low-light camera and a lidar to provide forward-view environmental state. In the meantime, we design panoramic mosaic algorithm, surround-view data fusion algorithm and forward-view data fusion algorithm. Besides, object detection algorithm is used to provide forward-view detection results. This driving assistance system will advance research into autonomous unmanned ground vehicles.
Who reads Driving Assistance System Based on Data Fusion of Multisource Sensors for Autonomous Unmanned Ground Vehicles?
It is typically read by researchers, students, and practitioners in Computer Science.
- Author
- Yang, Jiachen (author);Liu, Shan (author);Su, Hansong (author);Tian, Ying (author)
- Publisher
- Elsevier BV
- Published
- 2021
- Language
- EN
- Field
- Computer Science (Physical Sciences)