NRP_grasping

ROS packages and models for learning to grasp in NRP using shadow hand and UR10

Prerequisites

sudo apt install ros-kinetic-controller-manager ros-kinetic-ros-controllers ros-kinetic-moveit

pip2.7 install tensorflow keras h5py sklearn bokeh bayesian-optimization pandas

Setup & compile

cd NRP_grasping
git submodule init
git submodule update --recursive
cp GazeboRosPackages/* $HBP/GazeboRosPackages/src -a
cp Models/* $HBP/Models/ -a # add folder names in models.txt if needed
cp Experiments/* $HBP/Experiments -a
cd $HBP/Models
./create-symlinks.sh

cd $HBP/GazeboRosPackages
catkin_make

Adjust GAZEBO_MODEL_PATH and MESH_WORKSPACE_PATH in smart_grasping_sandbox/launch/smart_grasping_sandbox.launch

Run

1. Starte the Neurorobotics Platform

cle-start
cle-frontend

2. Load robot description, start moveit and gazebo2moveit nodes

roslaunch smart_grasping_sandbox smart_grasping_sandbox.launch

3. Open the shadow experiment (do not start the simulation yet)
4. Load controllers

roslaunch fh_desc controllers.launch

5. Start simulation in NRP
6. Fire up python sample RL python script

roscd smart_grasping_sandbox/scripts
python RL-hand.py