摘要
为提升餐厅送餐系统的智能化程度,依托NVIDIA Jetson Nano b01的ROS移动机器人平台,设计用于室内餐厅的AI送餐软件系统。该系统基于轻量级深度学习框架Darknet,采用C++和Python进行系统编程,包含控制器、语音、运动控制和AI视觉处理4个模块。通过语音启动送餐机器人,在识别顾客订餐信息二维码后,自主导航至目标餐桌进行送餐。同时,基于YOLOv3-tiny深度学习对送餐沿途上的人物进行视觉识别,当识别到顾客时语音播报欢迎词。实验结果表明,该系统能有效完成送餐任务,二维码识别时间约0.003s,人物识别准确率高达99%以上。系统能够自动进行语音启动和播报,设计方案合理有效,可为AI送餐领域提供参考与借鉴。
In order to improve the intelligence of the restaurant delivery system, relying on the ROS mobile robot platform of NVIDIA Jetson Nano b01, the AI delivery software system for indoor restaurants is designed. Based on the lightweight deep learning framework Darknet, the system is programmed with C + + and Python. It includes four modules: controller, voice, motion control and AI visual processing. Start the food delivery robot by voice, and after recognizing the QR code of customer ordering information, navigate to the target table to deliver food. At the same time, people along the way of food delivery are visually recognized based on YOLOv3 tiny deep learning, and welcome words are broadcast by voice when customers are recognized. The experimental results show that the system can effectively complete the meal delivery task, the two-dimensional code recognition time is about 0.003s, and the character recognition accuracy is up to 99%. The system can automatically start and broadcast voice, and the design scheme is reasonable and effective, which can provide reference for the AI food delivery field.
作者
罗中杉
李健
刘丹丹
LUO Zhong-shan;LI Jian;LIU Dan-dan(College of You Pei,Yancheng Institute of Technology;College of Electrical Engineering,Yancheng Institute of Technology,Yancheng 224051,China)
出处
《软件导刊》
2022年第12期128-132,共5页
Software Guide
基金
江苏省大学生创新训练计划项目(2021031)。
