摘要
针对在同步定位与地图构建系统中,使用单一的视觉或激光传感器时,容易出现采集的图像特征信息不准确或丢失,从而导致定位失败的问题,提出一种基于传感器融合的同步定位与地图构建方法。通过将惯性传感器获取的惯性里程计、深度相机获取的视觉里程计与伺服电机编码器获取的轮式里程计融合,共同构成系统状态参数及系统协方差矩阵,并使用扩展卡尔曼滤波方法构建多传感器融合的同步定位与地图构建系统。实验结果表明:与传统的同步定位与地图构建系统相比,该方法能够提高定位精度,改善移动平台的运动性能。
In the synchronous positioning and map building system,when a single vision or laser sensor is used,the collected image feature information is easy to be inaccurate or lost,resulting in positioning failure.A synchronous positioning and map building method was proposed based on sensor fusion.By fusing the inertial odometer obtained by an inertial sensor,the visual odometer obtained by the depth camera and the wheel odometer obtained by servo motor encoder,the system state parameters,and system covariance matrix were formed together,and the extended Kalman filter method was used to construct the multi-sensor fusion synchronous positioning and map construction system.The experimental results show that compared with the traditional synchronous positioning and map building system,this method improves the positioning accuracy and the motion performance of the mobile platform.
作者
邓张
王吉芳
黄荣锐
马飞
DENG Zhang;WANG Jifang;HUANG Rongrui;MA Fei(Mechanical Electrical Engineering School,Beijing Information Science&Technology University,Beijing 100192,China)
出处
《北京信息科技大学学报（自然科学版）》
2021年第4期88-94,共7页
Journal of Beijing Information Science and Technology University
基金
促进高校内涵发展重点培育项目(5212010925)
北京信息科技大学研究生科技创新项目(5121911047)。
