This repos implements the method for the master thesis "Learning Task-parametrized Riemannian Motion Policies" from demonstrations. The thesis can be founded at:
https://elib.uni-stuttgart.de/handle/11682/11936
The installation is simple, please choose your directory that you want to save tp-rmp
repo and change to that directory. Then type:
git clone https://github.com/humans-to-robots-motion/tp-rmp
cd tp-rmp
pip install -r requirements.txt
Additonally, please install ffmpeg
by:
sudo apt install ffmpeg
We create a dataset of 2D skills consisting of start
frame and end
frame
For 2D virtual point system setting, to see the reproduction the following 2D skill:
under moving end
frame in circle, please run:
python scripts/test_tprmp_2d_moving.py
to see the reproduction under moving end
frame in circle and avoiding obstacle, please run:
python scripts/test_tprmp_2d_moving_rmpflow.py
For 6-DoFs UR5 robot arm setting, to see the reproduction of picking skill under dynamic task situations, e.g. pick moving object, please run:
python scripts/test_tprmp_moving.py
For additionally avoiding obstables, please run:
python scripts/test_tprmp_with_rmpflow_moving.py