Update README.md

Author: Ryohei Sasaki

README.md

@@ -1,41 +1,36 @@
-[![Build Status](https://travis-ci.com/yukkysaito/amcl_3d.svg?branch=master)](https://travis-ci.com/yukkysaito/amcl_3d)
-
-I develop this package every weekend.
-
-# Work in progress
-90%
-
-# Install Requirements
-
-```
-$ git clone https://github.com/yukkysaito/amcl_3d.git <catkin_ws/src path>
-$ rosdep install --from-paths <amcl_3d path> -y
-```
-
-# TODO
-- add prediction model (particle filter)
-
-# Done
-- design interface (particle filter)
-- make ros package template
-- add basic resample function (particle filter)
-- add init function(particle filter)
-- build check (travis ci)
-- resampling timing based on ESS (effective sample size)
-- add simple likelihood model for lidar measurement (particle filter)
-- implement argumented mcl
-- implement kld sampling
-
-# Reference
-## English Reference
-### General
-- http://www.probabilistic-robotics.org/
-### Effective Sampling Size
-- http://www.cns.nyu.edu/~eorhan/notes/particle-filtering.pdf
-### Avoidance Numerical Underflow
-- http://www.maths.lu.se/fileadmin/maths/forskning_research/InferPartObsProcess/particlemethods.pdf
-
-## Japanese Reference
-- http://lab.cntl.kyutech.ac.jp/~nishida/lecture/psc/no11.pdf
-- https://gihyo.jp/book/2018/978-4-7741-9646-6
-- https://qiita.com/MoriKen/items/dfb6eb168649873589f0
+[![Build Status](https://travis-ci.com/yukkysaito/amcl_3d.svg?branch=master)](https://travis-ci.com/yukkysaito/amcl_3d)
+
+AMCL(Adaptive Monte Carlo Localization) in 3D for ROS.
+
+# Install Requirements
+
+```
+$ git clone  https://github.com/rsasaki0109/amcl_3d <catkin_ws/src path>
+$ rosdep install --from-paths <amcl_3d path> -y
+```
+
+# Demo
+
+```
+wget https://openspur.org/~atsushi.w/dataset/mcl_3dl/short_test.bag
+```
+
+```
+roslaunch amcl_3d amcl_3d_rosbag.launch
+```
+
+![demo](./gif/demo.gif) 
+
+# Reference
+## English Reference
+### General
+- http://www.probabilistic-robotics.org/
+### Effective Sampling Size
+- http://www.cns.nyu.edu/~eorhan/notes/particle-filtering.pdf
+### Avoidance Numerical Underflow
+- http://www.maths.lu.se/fileadmin/maths/forskning_research/InferPartObsProcess/particlemethods.pdf
+
+## Japanese Reference
+- http://lab.cntl.kyutech.ac.jp/~nishida/lecture/psc/no11.pdf
+- https://gihyo.jp/book/2018/978-4-7741-9646-6
+- https://qiita.com/MoriKen/items/dfb6eb168649873589f0