Research on autonomous driving perception based on deep learning algorithm

Bolin Zhou; Jihu Zheng; Chen Chen; Pei Yin; Yang Zhai

doi:10.1117/12.2539133

27 November 2019 Research on autonomous driving perception based on deep learning algorithm

Bolin Zhou, Jihu Zheng, Chen Chen, Pei Yin, Yang Zhai

Proceedings Volume 11321, 2019 International Conference on Image and Video Processing, and Artificial Intelligence; 113210B (2019) https://doi.org/10.1117/12.2539133
Event: The Second International Conference on Image, Video Processing and Artifical Intelligence, 2019, Shanghai, China

Abstract

Multiple source sensor fusion is the foundation of motion planning for autonomous driving system, which is the crucial part in improving the performances for unmanned operational system. In this article, based on the deep learning platform CATARC constructed, applied with Udacity’s Lincoln MKZ multiple sensor data, implemented with Robotic Operation System, Computer Vision, PointCloud Library, Deep Neural Networks and Extended Kalman Filter, constructed a low-cost object pose estimation data fusion solution, aiming at technic support for the industrialization of autonomous driving technologies.

Citation Download Citation

Bolin Zhou, Jihu Zheng, Chen Chen, Pei Yin, and Yang Zhai "Research on autonomous driving perception based on deep learning algorithm", Proc. SPIE 11321, 2019 International Conference on Image and Video Processing, and Artificial Intelligence, 113210B (27 November 2019); https://doi.org/10.1117/12.2539133

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