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因子图 || 协同导航

url: https://ar5iv.labs.arxiv.org/html/2107.01602?_immersive_translate_auto_translate=1
title: "Graphical State Space Model"
description: "In this paper, a new framework, named as graphical state space model, is proposedfor the real time optimal estimation of one kind of nonlinear state space model.By discretizing this kind of system model as anequatio…"
host: ar5iv.labs.arxiv.org
image: https://ar5iv.labs.arxiv.org/assets/ar5iv_card.png

开源地址

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基于因子图和最大熵的多AUV协同定位
Cooperative Positioning for Multi-AUVs Based on Factor Graph and Maximum Correntropy

基于改进因子图和和积理论的多AUV先进协同定位算法
An Advanced Cooperative Positioning Algorithm Based on Improved Factor Graph and Sum-Product Theory for Multiple AUVs

基于因子图的AUV协同导航算法
AUV cooperative navigation algorithm based on factor graph

使用拓扑因子图进行船舶和水下航行器协同定位
Vessel and Underwater Vehicles Cooperative Localization using Topology Factor Graphs

基于异步相对观测的多自主水下航行器协同定位
Multiple Autonomous Underwater Vehicles Cooperative Localization Based on Asynchronous Relative Observation

使用多个自主水下航行器的协作定位和未知现状估计
Cooperative Localization and Unknown Currents Estimation Using Multiple Autonomous Underwater Vehicles

Factor graphs and the sum-product algorithm

基于模型的信号处理的因子图方法
The Factor Graph Approach to Model-Based Signal Processing