alias python='python3'
#학습
./isaaclab.sh -p source/standalone/workflows/rsl_rl/train.py --task Isaac-Throw-Cube-Franka-v0 --num_envs 4096 --headless
#학습과정보기
./isaaclab.sh -p -m tensorboard.main --logdir logs/rsl_rl/franka_throw/
#학습된policy실행
#100회
./isaaclab.sh -p source/standalone/workflows/rsl_rl/play.py --task Isaac-Throw-Cube-Franka-v0 --num_envs 32 --load_run 2024-08-01_22-26-16 --checkpoint model_200.pt
#700회
./isaaclab.sh -p source/standalone/workflows/rsl_rl/play.py --task Isaac-Throw-Cube-Franka-v0 --num_envs 32 --load_run 2024-08-01_19-31-21 --checkpoint model_400.pt
#1499회
./isaaclab.sh -p source/standalone/workflows/rsl_rl/play.py --task Isaac-Throw-Cube-Franka-v0 --num_envs 32 --load_run 2024-08-01_19-31-21 --checkpoint model_1499.pt
franka>agents>rsl_rl_cfg.py
ㄴ clip parameter : clip_param
ㄴ PPO learning epoch : num_learning_epochs
ㄴ Critic Loss Coeff: value_loss_coef
ㄴ Diacount Factor: gamma
ㄴ Gradient Norm.: max_grad_norm
ㄴ Adapt LR :
# step a: collect data with keyboard
./isaaclab.sh -p source/standalone/workflows/robomimic/collect_demonstrations.py --task Isaac-Throw-Cube-Franka-IK-Rel-v0 --num_envs 1 --num_demos 10 --device keyboard
# step b: inspect the collected dataset
./isaaclab.sh -p source/standalone/workflows/robomimic/tools/inspect_demonstrations.py logs/robomimic/Isaac-Throw-Cube-Franka-IK-Rel-v0/hdf_dataset.hdf5
# install the dependencies
sudo apt install cmake build-essential
# install python module (for robomimic)
./isaaclab.sh -i robomimic
# split data
./isaaclab.sh -p source/standalone//workflows/robomimic/tools/split_train_val.py logs/robomimic/Isaac-Throw-Cube-Franka-IK-Rel-v0/hdf_dataset.hdf5 --ratio 0.2
./isaaclab.sh -p source/standalone/workflows/robomimic/train.py --task Isaac-Throw-Cube-Franka-IK-Rel-v0 --algo bc --dataset logs/robomimic/Isaac-Throw-Cube-Franka-IK-Rel-v0/hdf_dataset.hdf5
./isaaclab.sh -p source/standalone/workflows/robomimic/play.py --task Isaac-Throw-Cube-Franka-IK-Rel-v0 --checkpoint /PATH/TO/model.pth