Improve turtlebot localization in simulation for real world experiments
Hey,
I am right now trying to implement some different reinforcement learning algorithms to my Turtlebot for navigational tasks. In preparation for transferring those after training to the real turtlebot, I am right now trying to make the localization "more real". Due to friction and slip effects, the robots simulated odometry data is not suitable to deliver "realistic" cooardinates for planning the path. Therefore I am looking for ways to make the simulation more realistic. I already have some thoughts about it:
I found out about the libgazebo_ros_diff_drive.so plugin which is used in simulation as a controller. There I can switch
<odometrySource>world</odometrySource>to<odometrySource>encoder</odometrySource>and I will get data from the encoder integration instead of from the gazebo world (and no perfect coordinates). Thus I hope I can get effects like slipping better into the simulation
Right now I am also thinking about using tf as well. If I have a look in RVIZ, I can see that the locations of the cooardinate systems of the Map and Odom start to differ with time. Here it might be useful to have a look at the rqt_tf_tree which has the followed structure (with encoder setting):
map => odom => base_footprint => base_link => wheel_left_link, wheel_right_link, lmu_link, base_scan, center_back_link
Would it here be sufficient to connect the both map and base_link directly in order to get a higher reality factor?
Would be great if you may also have some ideas of how to make the localization of the robot more realistic.
Kind regards Marcel
