摘要
随着智慧民航的提出与建设,机务维修作业智能化的要求被提出。在机库环境中引入SLAM(同时定位与建图)技术,可为无人机、智能移动机器人等提供有效的三维场景地图,使得智能设备能够更好地协助工作人员完成日常工作,在极大降低工作负担的同时大幅提升工作效率。SLAM作为智能移动机器人导航技术的一部分,可以完成其在机库环境下的同时定位与建图。该文根据SLAM技术的发展现状结合机库环境的特点,深度分析机库环境下无人机、智能小车等移动机器人SLAM技术的实现方案,并作出相关展望,最终得出采用引入深度学习的视觉惯性SLAM技术可满足该特殊场景需求的结论。
With the proposal and construction of intelligent civil aviation,the requirement of intelligent maintenance operation has been put forward.The introduction of SLAM technology into the hangar environment can provide effective three-dimensional scene maps for drones and intelligent mobile robots,so that intelligent devices can better assist staff to complete their daily work,greatly reduce the workload and greatly improve work efficiency.As a part of intelligent mobile robot navigation technology,SLAM can complete its simultaneous positioning and mapping in the hangar environment.According to the development status of SLAM technology and the characteristics of hangar environment,this paper deeply analyzes the implementation scheme of SLAM technology of UAV,intelligent car and other mobile robots in hangar environment and makes relevant prospects.Finally,it is concluded that the visual inertia SLAM technology with deep learning can meet the needs of this special scene.
作者
成鹏
罗文田
刘莉雯
CHENG Peng;LUO Wentian;LIU Liwen
出处
《科技创新与应用》
2023年第28期16-18,23,共4页
Technology Innovation and Application
基金
中央高校基本科研业务费基金项目(J2022-07)。
关键词
机务维修
无人机
智能移动机器人
同时定位与建图
深度学习
aircraft maintenance
UAV
intelligent mobile robot
simultaneous positioning and mapping
deep learning
