Dear all,

We'd like to announce our information-theoretic mapping and
exploration package for Turtlebot. The package was designed to
enable autonomous 3D mapping and exploration for the Turtlebot over
indoor environments, by evaluating
information gain over a set of selected candidate view points. It currently
supports mapping with a Kinect sensor as well as localizing with the same
Kinect sensor using gmapping. All the computation may be performed on
the Turtlebot laptop and the resulting 3D map will be saved in octomap
format(.ot).

A short video of the method's performance can be found here (video played
10X faster): https://youtu.be/swWLNHOefg0

Please find the source code and tutorial here:
https://github.com/RobustFieldAutonomyLab/turtlebot_exploration_3d

Please feel free to provide feedback or suggestions <here>
<https://github.com/RobustFieldAutonomyLab/turtlebot_exploration_3d/issues>;
we hope you will find it useful!


Shi Bai
PhD Candidate
Robust Field Autonomy Lab <http://personal.stevens.edu/~benglot>
Stevens Institute of Technology