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引用次数: 0
摘要
本文介绍了一种具有基于摄像头的车道检测功能和交通信号/障碍物、行人识别功能的自主微型机器人汽车。机器人操作系统2 (Robot Operating System 2, ROS2)是机器人系统开发的中间件。不需要驾驶员的自动驾驶不仅需要车道跟随驾驶，还需要交通信号识别和障碍物识别。在FPGA上实现了这些功能，并对其进行了评估。根据这些结果，FPGA的交通信号识别执行时间比CPU的执行时间快1.2 ~ 3.4倍。使用YOLOv4进行障碍物识别，与YOLOv4 - tiny相比，mAP提高了3.79分。
Desgin and Implementation of ROS2-based Autonomous Tiny Robot Car with Integration of Multiple ROS2 FPGA Nodes
This paper introduces an autonomous tiny robot car equipped with a camera-based lane detection function and a traffic signal/obstacle, pedestrian recognition function. Each function is integrated by Robot Operating System 2 (ROS2), a middleware for robot system development. Autonomous driving without the need for a driver requires not only lane-following driving but also traffic signal recognition and obstacle recognition. These functions are implemented on FPGA, and we evaluated them. According to these results, the execution time of traffic signal recognition by FPGA was 1.2 to 3.4 times faster than CPU execution. YOLOv4 is used for obstacle recognition, which improved mAP by 3.79 points compared to YOLO v3-Tiny.
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