Target detection and positioning method based on lightweight convolutional neural network

Abstract

The invention relates to a target detection and positioning method based on a lightweight convolutional neural network, which belongs to the technical field of deep learning, and solves the problem that an existing method cannot meet the requirement of the real-time processing of an unmanned vehicle. The method comprises the steps of collecting the image data and the point cloud data in front of avehicle in real time; transmitting the image data to a target detection model, carrying out target identification, and obtaining the target information, wherein the target detection model adopts thelightweight convolutional neural network; and inputting the obtained target information and the point cloud data into the trained target positioning model, and carrying out target positioning to obtain the position information of the target relative to the vehicle. According to the method, the real-time detection and positioning of the static and dynamic targets are realized, so that the vehicle can sense the target information in real time, the obstacle avoidance processing is conducted on the target in time, the detection and recognition result has the higher accuracy, the method can be usedfor the complex scenes with a plurality of static and dynamic targets, and the real-time detection and positioning requirement of the automatic driving vehicle is met.

Description

technical field [0001] The invention relates to the technical field of deep learning, in particular to a target detection and positioning method based on a lightweight convolutional neural network. Background technique [0002] The use of deep learning in multi-sensor data processing such as machine vision and lidar information is attracting the attention of more and more researchers and is being gradually applied to products. Target detection and localization is one of the core perception technologies of unmanned vehicles, which can be subdivided into two parts: target detection and target localization. Among them, the target detection is to realize the detection and recognition of the target in the image, and the target positioning is to realize the distance information of the target relative to the sensor. For target detection and positioning technology, traditional methods and highly complex convolutional neural networks are currently used to achieve. [0003] In the t...

AI Technical Summary

Problems solved by technology

[0004] In view of the above analysis, the present invention aims to provide a target detection and positioning method based on a lightweight convolutional neural network to solve the problem that existing target detection and recognition methods cannot meet the real-time requirements of unmanned vehicles

Images