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state_estimation's Introduction

State Estimation


[TOC]

1. Probability Theory and Statistics

MAP, MLE & MLS

  • MAP (Maximum A Posteriori)

  • MLE (Maximum Likelihood Estimate)

    • 模型已定,参数未知:找出一组参数,使得模型产生出观测数据的概率最大,即找出一组能使似然函数最大的参数
  • MLS (Minimum Least Squares)

RANSAC (RANdom SAmple Consensus)

M-Estimator

  • M-estimators

  • MLESAC: A New Robust Estimator with Application to Estimating Image Geometry

Probabilistic Graphical Models

Factor Graph

Bayesian Network

Markov Random Fields

2. Filters

3. Optimization

Basics

  • Gauss Newton

  • Levenberg-Marquadt

    • sparseLM : Sparse Levenberg-Marquardt nonlinear least squares in C/C++
  • ESM

Optimizer

Bundle Adjustment

Sparse Hessian matrix :

4. Dataset

BAL Dataset

  • Bundle Adjustment in the Large

g2o Dataset

5. Books

state_estimation's People

Contributors

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