The features of machine learning in lidar data processing are described

What is it about?

The article discusses the elements of systems for ensuring autonomous driving of electric vehicles, the main emphasis is placed on the processing of lidar data using various neural network architectures, such as PointNet, Dynamic Graph CNN, recurrent neural networks (RNN), convolutional neural networks (CNN). The benefits of implementing machine learning methods in lidar applications are discussed, which can improve the safety and efficiency of autonomous electric vehicles. Tasks such as object recognition with interference filtering are considered. The paper substantiates the need for further research and development of noise reduction systems to improve the reliability and sustainability of autonomous lidar systems in real-world conditions.

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Why is it important?

The importance of this issue is driven by the developing market for autonomous vehicles.

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