Hi All, the conceptual aspects are well explained under my point of view.
However a step by step should be explained.
In part 1, it showed how to create Robot Environment and binding to Gazebo environment in a local package.
In part 2, it refers to the ready environments contained in open_ai package.
I think the target is to do everything from scratch and the unit7 bypasses some aspect as it assumes that some things are known (msg creation , recompilation , cmake changes other configuration … of course these are thoroughly explained in other learning paths but it enforces to delve deep and makes the abstract learning very difficult)
If the student/learner wants to understand deeper what he is doing in the step by step, its up to him to explore the other learning paths.
Here are other of following reasons.
Part 1-2 are a full round up of different concepts like:
- List item
- ROS Core
- messages + catkin cmake
- publish -subscribe (Ros basics )
- mechanical definition (URDF modelling + Collision engine for Gazebo)
- decoupling python 2.7(only for ROS components) and python 3.5
- RL concepts (available to in openAI)
I think the target of this unit is to show the learner how to integrate any RL algorithm in a ROS environment and all the aspect that have to be taken into account.
I don’t see clearly how i can apply analogously this unit to another ROS environment with another robot with another task (except by delving deep into the other resources) because this unit is a bit “foggy”
Think about the following issue. Imagine i would like to apply an ppo reinforcement algorithm with another ROS model and environment with a defined target.
This is just an opinion for these last unit.
So in other words, can we have the correction of
Exercice 7.3 7.4 and 7.5
In all cases congratulations to the whole team