基于EdgeBoard的AI视觉多功能智能车的设计与实现

Design and Implementation of Visual Multifunctional Intelligent Vehicle Based on Baidu Edgeboard Computing Board and Wobot Controller

以百度飞桨PaddlePaddle作为运算平台,采用卷积神经网络算法构建数据模型,对智能车赛道数据进行了采集和处理,并基于百度深度学习开源平台AI Studio进行模型训练,完成对车道数据的检测.本系统实现了将赛道检测的人工智能技术与传统运用传感器进行侧面标识物的检测相结合,最终完成基于百度EdgeBoard计算板和Wobot控制器的视觉多功能智能车的设计与实现.

A data model using convolution neural network algorithm based on Baidu PaddlePaddle is constructed to collect and process the track data.A corresponding model training based on AI studio is conducted for the AI learning and training community of propeller on Baidu deep learning open source platform.The detection and processing of lane data is completed.The system combines the artificial intelligence technology of track detection with the traditional use of sensors for the detection of side markers,and finally completes the design and implementation of visual multifunctional intelligent vehicle based on Baidu Edgeboard computing board and Wobot controller.