Iterative training problems
Hi gazebo-community, as i am trying to implement a neuroevolutionary method using gazebo as a simulator i am running into the same problem for quite some weeks now:
When trying to reset the simulation / the robot to always have the same starting positions everything works fine from a visual point of view. The robot "jumps" back into its original position when i call ->reset_simulation / world. Still i always get different results even tho i use the same pattern every iteration. I read some questions on this forum regarding the same problem, but none of those come up with a working solution (at least for me).
I tried deleting and respawning the model, which leaks memory and causes a segfault after some time. I tried calling different resets, resetting via commandline and also via ROS topic.
I read one answert stating this kind of iterative training is not possible in gazebo. Did this change lately or is my approach generally wrong?
Thanks in advance
