利用艾特金加速法和扩展卡尔曼滤波算法递归重新定位丢失智能体

Proceedings of the 2021 2nd International Conference on Artificial Intelligence in Electronics Engineering Pub Date : 2021-01-15 DOI:10.1145/3460268.3460282

Lei Sun, Xiao Yang, Guizhen Wang

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引用次数: 0

摘要

利用信号与噪声的状态空间模型寻找多个移动智能体的缺失位置。利用其他移动agent的估计值和当前观测值对状态变量的估计值进行更新，得到移动agent缺失位置的估计值。为了提高迭代方法的收敛速度，采用扩展卡尔曼滤波算法和艾特金加速收敛法，用所有丢失的位置递归移动智能体的位置。

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Recursive relocation of lost intelligent agent by Aitkin acceleration method and extended Kalman filtering algorithm

The state space model of signal and noise is used to find the missing position of multiple mobile intelligent agents. The estimation value of other mobile agents and the observed value at the present time are used to update the estimation of the state variable, and the estimation value of the missing position of mobile agents is obtained. In order to improve the convergence speed of the iterative method, the extended Kalman filtering algorithm and the aitkin accelerating convergence method are used to recurse the location of the mobile agent with all the lost positions.

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Proceedings of the 2021 2nd International Conference on Artificial Intelligence in Electronics Engineering

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