首页|基于ROS操作系统的智能家居机器人

基于ROS操作系统的智能家居机器人

扫码查看
现如今,我国人口老龄化日趋严重,智能家居机器人对提高生活质量、辅助独居老人和残疾人生活有积极作用.但是市面上的家庭服务机器人的功能还不够完善,能够独立完成自主巡检和家庭服务的AI机器人还很缺乏,所以我们设计了一款基于ROS操作系统的智能家居机器人.研究旨在通过智能家居机器人提高用户的生活质量,包括自动化日常家务、提供娱乐和陪伴,以及增强居家安全.通过智能管理家居能源使用和减少浪费,促进环境可持续发展.智能家居机器人设计由智能识别单元、构建地图单元、定位分拣单元等部分组成,应用先进的人工智能识别技术,激光雷达构图技术,针对存在危险物与苛刻环境进行准确构图,识别危险物并用机械手臂进行排除.智能家居机器人的研究不断进步,旨在更好地融入人们的日常生活,提供更加智能、便捷和舒适的居住环境.随着技术的发展,未来的智能家居机器人将能够提供更加丰富和精细化的服务.
Smart Home Robot Based on ROS Operating System
Nowadays,population aging in our country is becoming more and more serious.Smart home robots play a positive role in improving the quality of life and assisting the life of elderly and disabled people living alone.However,the functions of home service robots on the market are not perfect enough,and there is still a lack of AI robots that can independently complete autonomous inspection and home service.Therefore,we designed a smart home robot based on ROS operating system.The research aims to improve users'quality of life through smart home robots,including automating daily chores,providing entertainment and companionship,and enhancing home safety.Promote environmental sustainability by intelligently managing home energy use and reducing waste.Smart home robot design is composed of intelligent identification unit,map building unit,positioning sorting unit and other parts,the application of advanced artificial intelligence recognition technology,Lidar composition technology,for the existence of dangerous objects and harsh environment for accurate composition,identification of dangerous objects and mechanical arm to exclude.The research of smart home robots continues to advance,aiming to better integrate into People's Daily life and provide a more intelligent,convenient and comfortable living environment.With the development of technology,future smart home robots will be able to provide more rich and refined services.

smart homeprinciple of SLAMoptical flow positioningdeep learning

赵恩波、于家旺、王晓鹏、常财超、曲强

展开 >

辽宁科技大学电子与信息工程学院 鞍山 114051

智能家居 SLAM原理 光流定位 深度学习

2024

日用电器
中国电器科学研究院有限公司

日用电器

影响因子:0.071
ISSN:1673-6079
年,卷(期):2024.(5)