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Pure Mathematics 2024
结合多维泰勒网策略优化EKF-SLAM算法一致性的新方法研究
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Abstract:
本文旨在非线性SLAM系统中设计一种改进的EKF-SLAM算法进行状态估计和构建一致性地图。通过引入多维泰勒网和第一估计雅可比矩阵方法，我们提出了一种新颖的估计算法，旨在提高系统的鲁棒性和构建地图的一致性。本研究首先介绍了多维泰勒网的基本原理，数学模型和EKF-SLAM算法的可观性分析，然后详细描述了改进的EKF-SLAM算法的设计和实现过程。我们通过仿真实验验证了该改进算法在非线性SLAM系统中的有效性和优越性，结果表明，该改进算法在对系统状态估计和构建一致地图方面有着很好的效果。
This manuscript aims to design an improved EKF-SLAM algorithm for state estimation and consistency map construction in nonlinear SLAM systems. By introducing multi-dimensional Taylor nets and the first estimate Jacobian matrix method, we propose a novel estimation algorithm aimed at improving the robustness of the system and the consistency of the constructed map. This manuscript first introduces the basic principle of multi-dimensional Taylor net, mathematical model and observability analysis of EKF-SLAM algorithm, and then describes the design and implementation process of improved EKF-SLAM algorithm in detail. The effectiveness and superiority of the improved algorithm in nonlinear SLAM system are verified by simulation experiments. The results show that the improved algorithm has a good effect on the estimation of the system and the construction of a consistent map.
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