摘要
精确鲁棒的定位系统是保证室内巡检机器人正常工作的重要基础。文章基于机器人操作系统(ROS),针对现有公开视觉算法ORB-SLAM2在低性能计算平台上因计算能力不足导致的特征跟踪丢失问题,提出一种将ORB-SLAM2与惯性导航系统(Inertial Navigation System,INS)解算误差进行卡尔曼滤波融合的方法。经公开数据集验证表明,该方法能够完整地估计出视觉失效时丢失的位姿信息,与ORB-SLAM2相比,定位系统的精度与鲁棒性有效提高。
Accurate and robust positioning system is an important basis to ensure the normal operation of indoor inspection robot.Based on the robot operating system(ROS),aiming at the loss of feature tracking caused by the insufficient computing power of the existing public vision algorithm ORB-SLAM2 on the low-performance computing platform,this paper proposes a method for Kalman filter fusion in the solution errors of ORB-SLAM2 and inertial navigation system(INS).The verification of public data sets shows that this method can completely estimate the pose information lost when visual failure.Compared with ORB-SLAM2,the accuracy and robustness of the positioning system are effectively improved.
作者
孙希君
王秋滢
王水根
吴应为
SUN Xijun;WANG Qiuying;WANG Shuigen;WU Yingwei(College of Information and Communication Engineering,Harbin Engineering University,Harbin 150001,China;College of Underwater Acoustic Engineering,Harbin Engineering University,Harbin 150001,China;Key Laboratory of Underwater Acoustic Technology,Harbin Engineering University,Harbin 150001,China;Yantai Iray Technology Co.,Ltd.,Yantai 264006,China)
出处
《现代信息科技》
2021年第13期139-143,147,共6页
Modern Information Technology
基金
国家自然科学基金(51879046)
黑龙江省自然科学基金(YQ2019F001)。
