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Cooperative Localization Using Fuzzy Decentralized Extended Information Filtering for Homogenous Omnidirectional Mobile Multi-robot System

机译:使用模糊分散扩展信息过滤的合作本地化,用于同质全透视移动多机器人系统

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This paper presents a cooperative map-based localization method using fuzzy decentralized extended information filtering (FDEIF) for a multi-robot system composed of multiple homogeneous omnidirectional mobile robots (OMRs). With the help of one KINECT-based landmark or QR code found by one robot, a pose initialization algorithm is applied to estimate both start-up positions and orientations of that robot, and a cooperative localization method is proposed to find initial poses of other robots that can be directly detected by a laser scanner mounted at this localized robot. Once the initial global poses of all robots have been roughly determined, an FDEIF dynamic cooperative localization method is proposed to fuse external measurements from one RGB-D sensor, or one laser scanner and four encoders mounted on each robot, in order to continuously keep track of the accurate moving poses of all the robots. Simulations are conducted to show that the proposed method is effective in finding accurate estimation of both unknown initial and continuous moving poses of three omnidirectional mobile robots in a team.
机译:本文介绍了一种基于地图的本地化方法,该方法使用模糊分散信息滤波(FDEIF),用于由多个同质全向移动机器人(OMRS)组成的多机器人系统。借助一个机器人发现的基于Kinect的地标或QR码,应用了姿势初始化算法来估计该机器人的启动位置和方向,并且提出了一种合作定位方法来查找其他机器人的初始姿势可以通过安装在该局部机器人的激光扫描仪直接检测。一旦粗略地确定了所有机器人的初始全局姿势,就提出了一种FDEIF动态协作定位方法,以熔断来自一个RGB-D传感器的外部测量,或者在每个机器人上安装一个激光扫描仪和四个编码器,以便连续跟踪轨道所有机器人的准确姿势的姿势。进行仿真以表明该方法是有效地在团队中找到三个全向移动机器人的未知初始和连续移动姿势的准确估计。

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