最小二乘函数近似
非线性最小二乘法
算法
递归最小平方滤波器
估计
计算机科学
估计员
估计理论
惯性测量装置
控制理论(社会学)
卡尔曼滤波器
广义最小二乘法
线性最小二乘法
迭代加权最小二乘法
应用数学
残差平方和
扩展卡尔曼滤波器
作者
Daniel Kubus,Torsten Kröger,F.M. Wahl
出处
期刊:Intelligent Robots and Systems
日期:2008-10-14
卷期号:: 3845-3852
被引量:37
标识
DOI:10.1109/iros.2008.4650672
摘要
The estimation of the ten inertial parameters of rigid loads, which are attached to manipulators, may benefit several robotics applications, e.g.: force control, object recognition, and pose estimation. These applications require sufficiently accurate, robust, and fast estimation of the inertial parameters. Existing approaches, however, do not allow for robust on-line estimation, since they use standard batch least-squares techniques, which ignore noise in the data matrix. The proposed approach, however, estimates the inertial parameters on-line and very fast (approx. 1.5s), while explicitly considering noise in the data matrix by a total least-squares approach. Apart from estimation equations and estimation approaches, the design of estimation trajectories is addressed in this paper. The performance of the proposed estimation approach is compared with the recursive ordinary least-squares (RLS) and the recursive instrumental variables (RIV) method. Experimental results clearly recommend the proposed recursive total least-squares approach (RTLS).
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