From e5c2ebe10bf48e6dc0a5cb864c43e5a83c911302 Mon Sep 17 00:00:00 2001 From: Atsushi Sakai Date: Sat, 3 Feb 2018 09:54:59 -0800 Subject: [PATCH] update README --- README.md | 17 ++++++++++++++++- 1 file changed, 16 insertions(+), 1 deletion(-) diff --git a/README.md b/README.md index ceca510e..354f43e7 100644 --- a/README.md +++ b/README.md @@ -5,13 +5,13 @@ Python codes for robotics algorithm. - # Table of Contents * [Requirements](#requirements) * [How to use](#how-to-use) * [Localization](#localization) * [Extended Kalman Filter localization](#extended-kalman-filter-localization) * [Unscented Kalman Filter localization](#unscented-kalman-filter-localization) + * [Particle Filter localization](#particle-filter-localization) * [Path Planning](#path-planning) * [Dynamic Window Approach](#dynamic-window-approach) * [Grid based search](#grid-based-search) @@ -104,6 +104,20 @@ Ref: - [Discriminatively Trained Unscented Kalman Filter for Mobile Robot Localization](https://www.researchgate.net/publication/267963417_Discriminatively_Trained_Unscented_Kalman_Filter_for_Mobile_Robot_Localization) +## Particle Filter localization + +![2](https://github.com/AtsushiSakai/PythonRobotics/blob/master/Localization/particle_filter/animation.gif) + +This is a sensor fusion localization with Particle Filter(PF). + +The blue line is true trajectory, the black line is dead reckoning trajectory, + +and the red line is estimated trajectory with PF. + +It is assumued that the robot can measure a distance from landmarks (RFID). + +This measurements are used for PF localization. + # Path Planning ## Dynamic Window Approach @@ -487,3 +501,4 @@ Atsushi Sakai ([@Atsushi_twi](https://twitter.com/Atsushi_twi)) +