This project aim at using the DDPG alogorithm in order to solve a simple graping problem with Baxter.
*Ros kinetic
*Baxter simulator: http://sdk.rethinkrobotics.com/wiki/Simulator_Installation
*Keras 1.2.2
*Tensorflow
*CUDA 8 - CUDNN 6 for training
Rq : a contact sensor has been added to baxter's left gripper check the file in /src/baxter_common/rethink_ee_description/urdf/electric_gripper/fingers/extended_narrow.xacro
*https://github.com/robosamir/ddpg-ros-keras
*https://robosamir.github.io/DDPG-on-a-Real-Robot/
*https://yanpanlau.github.io/2016/10/11/Torcs-Keras.html
The approach from https://robosamir.github.io/DDPG-on-a-Real-Robot/ has been adapted in order to control the speed of the robot and not the position
Here the reaching task only has been solved. The concerned files are in the reaching folder of the ddpg package. (cf ddpg.py and new_robotGame.py)
*roslaunch baxter_sim_examples baxter_ddpg.launch
*rosrun ddpg ddpg
Rq in ddpd use play(0) for replay and play(1) for training
Reaching the cube ok