Created an empty package that will hold the MCL implementation
In the process of creating a class that implements the MCL algorithm.

Need to finish sensorUpdate and then test.
Added a unit test file for the PoseCloud2D class.
created a localization_2d node that will use the PoseCloud2D class
to perform localization. Basic framework is set up. Need to test it out
and finish implementing the sensorUpdate method of PoseCloud2D.
Fixed the initial pose topic name.
Fixed sampling variance issue with low variance sampling algorithm
from table 4.4 on page 110 of the Probabilistic Robotics Textbook.
bunch of changes while debugging why the point cloud doesn't converge
properly.
Created Likelihood field message and calculator.
Created a node that publishes a saved likelihood field
Updated the PoseCloud2D to use likelihood fields instead of beam based
sensor model.
still not converging to the correct value. Going to try adding
in extra samples using the augemented MCL algorithm.
more tweaks.
Implemented the augmented MCL algorithm from the book.
Still not working.
Resampling is working properly. So its something in the measurementProbability
method that is messing up
localization is working when its guaranteed that the true pose
is included in the points. I think that if I remove that guarantee and
start including more new random points that this will be working.
Most of the issues were because the pose estimate transforms were
off by 90 degrees. In the map frame they were aligned with the y axis of
the base_link frame, but the tf transform works off of the x-axis.
Fixed some more bugs. Global localization seems to be working now
Now changing the number of samples via parameters.
Increased the velocity callback buffer
Split the PoseCloud into a base class, a class for 2D and a yet to
be implemented class for 3D