Mobile robot systems performing simultaneous localization and mapping(SLAM) are generally plagued by non-Gaussian noise.To improve both accuracy and robustness under non-Gaussian measurement noise,a robust SLAM algori...Mobile robot systems performing simultaneous localization and mapping(SLAM) are generally plagued by non-Gaussian noise.To improve both accuracy and robustness under non-Gaussian measurement noise,a robust SLAM algorithm is proposed.It is based on the square-root cubature Kalman filter equipped with a Huber' s generalized maximum likelihood estimator(GM-estimator).In particular,the square-root cubature rule is applied to propagate the robot state vector and covariance matrix in the time update,the measurement update and the new landmark initialization stages of the SLAM.Moreover,gain weight matrices with respect to the measurement residuals are calculated by utilizing Huber' s technique in the measurement update step.The measurement outliers are suppressed by lower Kalman gains as merging into the system.The proposed algorithm can achieve better performance under the condition of non-Gaussian measurement noise in comparison with benchmark algorithms.The simulation results demonstrate the advantages of the proposed SLAM algorithm.展开更多
The New Magnitude National Standard of General Rules for Earthquake Magnitude( GB17740-2017) is the state mandatory standard. It was released on May 12,2017,by the General Administration of Quality Supervision,Inspect...The New Magnitude National Standard of General Rules for Earthquake Magnitude( GB17740-2017) is the state mandatory standard. It was released on May 12,2017,by the General Administration of Quality Supervision,Inspection and Quarantine of the Peoples Republic of China and the Standardization Administration of the Peoples Republic of China. This paper introduces the necessity of revising the national standard of magnitude,and the main contents,technical points and primary features of the new national standard of magnitude,so that it can be applied better in practice.展开更多
针对移动机器人的同时定位与地图构建(Simultaneous Localization and Mapping,SLAM)问题,传统后端优化算法比较依赖于前端传感器构造位姿图,而且对于假阳性环形闭合约束鲁棒性较低。基于此,提出了一种鲁棒后端优化算法。利用因子图建立...针对移动机器人的同时定位与地图构建(Simultaneous Localization and Mapping,SLAM)问题,传统后端优化算法比较依赖于前端传感器构造位姿图,而且对于假阳性环形闭合约束鲁棒性较低。基于此,提出了一种鲁棒后端优化算法。利用因子图建立SLAM的优化模型,在使用新的鲁棒代价函数基础上引入先验约束用于确认启用或关闭前端传递的环形闭合约束,从而使得后端拓扑图能够摒弃前端传递的假阳性环形闭合约束并朝向真实地图收敛,再利用L-M(Levenberg-Mar-quardt)算法进行优化使其收敛到真实地图。仿真结果表明,SLAM后端优化算法缩小了前端数据和后端优化之间的差距,满足移动机器人精确定位与建图的需求。展开更多
数据关联是智能车同时定位与建图(simultaneous localization and mapping,SLAM)中的一个难点问题.为了快速准确获得数据关联结果,结合连续兼容最近邻(sequential compatibility nearest neighbor,SCNN)算法简单易实现和联合兼容分支定...数据关联是智能车同时定位与建图(simultaneous localization and mapping,SLAM)中的一个难点问题.为了快速准确获得数据关联结果,结合连续兼容最近邻(sequential compatibility nearest neighbor,SCNN)算法简单易实现和联合兼容分支定界(joint compatibility brarch and bound,JCBB)算法最优理念强的优点,提出了一种快速联合数据关联(fast joint data association,FJDA)算法.该算法首先在局部地图中采用SCNN数据关联算法处理所有的观测-特征对,得到关联结果;其次判断关联结果的准确性,若关联出错,则采用具有噪声的基于密度的聚类方法(densitybased spatial clustering of applications with noise,DBSCAN)对当前时刻的观测量进行分组,然后在每一小组中采用JCBB算法进行数据关联,最终将每一小组的关联解融合得到最终的关联结果.通过仿真实验对提出的算法、SCNN算法以及JCBB算法的性能进行了比较,结果表明提出的关联算法实时性强,准确度高.展开更多
基金Supported by the National High Technology Research and Development Program of China(2010AA09Z104)the Fundamental Research Funds of the Zhejiang University(2014FZA5020)
文摘Mobile robot systems performing simultaneous localization and mapping(SLAM) are generally plagued by non-Gaussian noise.To improve both accuracy and robustness under non-Gaussian measurement noise,a robust SLAM algorithm is proposed.It is based on the square-root cubature Kalman filter equipped with a Huber' s generalized maximum likelihood estimator(GM-estimator).In particular,the square-root cubature rule is applied to propagate the robot state vector and covariance matrix in the time update,the measurement update and the new landmark initialization stages of the SLAM.Moreover,gain weight matrices with respect to the measurement residuals are calculated by utilizing Huber' s technique in the measurement update step.The measurement outliers are suppressed by lower Kalman gains as merging into the system.The proposed algorithm can achieve better performance under the condition of non-Gaussian measurement noise in comparison with benchmark algorithms.The simulation results demonstrate the advantages of the proposed SLAM algorithm.
基金the Regular Project of China Earthquake Administration(16A43ZX014)
文摘The New Magnitude National Standard of General Rules for Earthquake Magnitude( GB17740-2017) is the state mandatory standard. It was released on May 12,2017,by the General Administration of Quality Supervision,Inspection and Quarantine of the Peoples Republic of China and the Standardization Administration of the Peoples Republic of China. This paper introduces the necessity of revising the national standard of magnitude,and the main contents,technical points and primary features of the new national standard of magnitude,so that it can be applied better in practice.
文摘针对移动机器人的同时定位与地图构建(Simultaneous Localization and Mapping,SLAM)问题,传统后端优化算法比较依赖于前端传感器构造位姿图,而且对于假阳性环形闭合约束鲁棒性较低。基于此,提出了一种鲁棒后端优化算法。利用因子图建立SLAM的优化模型,在使用新的鲁棒代价函数基础上引入先验约束用于确认启用或关闭前端传递的环形闭合约束,从而使得后端拓扑图能够摒弃前端传递的假阳性环形闭合约束并朝向真实地图收敛,再利用L-M(Levenberg-Mar-quardt)算法进行优化使其收敛到真实地图。仿真结果表明,SLAM后端优化算法缩小了前端数据和后端优化之间的差距,满足移动机器人精确定位与建图的需求。
文摘数据关联是智能车同时定位与建图(simultaneous localization and mapping,SLAM)中的一个难点问题.为了快速准确获得数据关联结果,结合连续兼容最近邻(sequential compatibility nearest neighbor,SCNN)算法简单易实现和联合兼容分支定界(joint compatibility brarch and bound,JCBB)算法最优理念强的优点,提出了一种快速联合数据关联(fast joint data association,FJDA)算法.该算法首先在局部地图中采用SCNN数据关联算法处理所有的观测-特征对,得到关联结果;其次判断关联结果的准确性,若关联出错,则采用具有噪声的基于密度的聚类方法(densitybased spatial clustering of applications with noise,DBSCAN)对当前时刻的观测量进行分组,然后在每一小组中采用JCBB算法进行数据关联,最终将每一小组的关联解融合得到最终的关联结果.通过仿真实验对提出的算法、SCNN算法以及JCBB算法的性能进行了比较,结果表明提出的关联算法实时性强,准确度高.
