摘要
针对机器人在室内、深海或者高楼林立的大都市导航定位存在的问题,该文展开了基于Xtion传感器与惯性测量单元(IMU)松组合的移动机器人室内定位算法的研究,采用了组合导航及自适应渐消扩展卡尔曼滤波算法等创新性方法,解决了机器人室内定位精度不高的问题。通过对机器人室内组合导航轨迹的实验验证,该文的组合导航方法能够提高机器人移动轨迹的精度,更接近于真实轨迹,满足了移动机器人室内导航定位的需求。
Aiming at the problem of navigation positioning in metropolitan indoors,deep seas or highrise buildings,this paper studied the mobile robot indoor positioning method based on the loose combination of Xtion sensor and inertial measurement unit(IMU).The research of localization algorithm adopts innovative methods such as integrated navigation and adaptive fading extended Kalman filter algorithm to solve the problem that the positioning accuracy of the robot is not high.Through the experimental verification of the combined navigation trajectory of the robot•the integrated navigation method of this paper could improve the accuracy of the robot’s moving trajectory and is closer to the real trajectory,which meets the needs of mobile robot indoor navigation and positioning.
作者
高明镜
郭杭
GAO Mingjing;GUO Haag(Information Engineering School of Nanchang University,Nanchang 330031,China)
出处
《测绘科学》
CSCD
北大核心
2020年第6期62-66,79,共6页
Science of Surveying and Mapping
基金
国家自然科学基金项目(41764002)
国家重点研发计划项目(2016YFB0502002)。
关键词
机器人
传感器
室内定位
松组合
robot
sensor
indoor positioning
loose combination
