View source for Ruben-RV-ROS01

* '''Project name:''' Turtlebot robot indoor navigation

* '''Dates:''' July 2013 - 

* '''Degree:''' Summer Research Residence

* '''Authors:''' Ruben 

* '''Contact:''' runix404@gmail.com

* '''SVN Repositories:''' 

* '''Tags:''' ROS, navigation, turtlebot

* '''Technologies:''' kinect, pcl, openni, c++, cmake, ROS

* '''State:''' Ongoing

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==ROS Fuerte Installation on Ubuntu 12.04==
===Repository configuration===

First we need to add the repository
<syntaxhighlight lang=Bash>sudo sh -c 'echo "deb http://packages.ros.org/ros/ubuntu precise main" > /etc/apt/sources.list.d/ros-latest.list'</syntaxhighlight>

and setup the keys
<syntaxhighlight lang=Bash>wget http://packages.ros.org/ros.key -O - | sudo apt-key add -</syntaxhighlight>

===Installation===
We need to refresh the cache of your package manager
<syntaxhighlight lang=Bash>sudo apt-get update</syntaxhighlight>

In our case, we decide to install ros-fuerte-desktop-full that is recommended in the ROS web, but you can also install other as explained on the [http://wiki.ros.org/fuerte/Installation/Ubuntu  web]

<syntaxhighlight lang=Bash>sudo apt-get install ros-fuerte-desktop-full</syntaxhighlight>


===Enviroment Configuration===

Now we need to configure the enviroment variables

<syntaxhighlight lang=Bash>echo "source /opt/ros/fuerte/setup.bash" >> ~/.bashrc </syntaxhighlight>

For refresh the enviroment variables of your terminal you can reset it or type

<syntaxhighlight lang=Bash> . ~/.bashrc </syntaxhighlight>

==Turtlebot installation==
The turtlebot installation is very simple, you only have to type in your terminal


<syntaxhighlight lang=Bash> sudo apt-get install ros-fuerte-turtlebot* </syntaxhighlight>

==Navigation==

=== Feasible Solutions ===

The feasible solutions are Dynamic Window and Potencial Field :

Dynamic Window : is a velocity-based local planner that calculates the optimal collision-free ('admissible') linear and angular velocity
for a robot required  to reach its goal

Potential-field : In the pontetial-field navigation each obstacle has an obstacle 'force field' for repelling the robot,
and the goal has a attraction fiel

=== Dynamic window algorithm ===



=== Experiments ===

In these experiments, the robot will try to reach the position (3,3) from the origin. 

1.
Simple scenario
[http://www.youtube.com/watch?v=_48PI78E-hg Simple navigation]

2.
A wall scenario 
[http://www.youtube.com/watch?v=nSkOCBKolfQ Navigation with obstacle]

3.
A realistic scenario

==Path Planning==

=== Voronoi ===

ongoing

=== Graph SLAM ===

ongoing