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StackForce SimReady Isaac Lab Export

This project was generated from StackForce SimReady and is ready to train in Isaac Lab / Isaac Sim.

Copy-Paste Training Commands

conda activate <your_isaac_lab_env_name>
cd <exported_project>
python -m pip install -e source/stackforce_simready_2foot_lab
python scripts/list_envs.py
python scripts/zero_agent.py --task Template-2foot-Direct-v0 --headless --num_envs 8
python scripts/rsl_rl/train.py --task Template-2foot-Direct-v0 --headless --num_envs 64 --max_iterations 100

If you want the Isaac Sim window to open, remove --headless.

Recommended Isaac Lab / Isaac Sim Environment

This export is recommended with the validated stack below:

Python 3.11
Isaac Sim 5.1.0
Isaac Lab v2.3.2 / pip 2.3.2.post1
Torch 2.7.0+cu128
Torchvision 0.22.0+cu128
LeggedGym-Ex 0.3.0 bundled rsl_rl

The export includes a one-click environment script:

chmod +x scripts/setup_stackforce_isaac_lab_sim_env.sh
./scripts/setup_stackforce_isaac_lab_sim_env.sh

The default environment name is env_isaaclab. Override it with:

ENV_NAME=my_isaaclab ./scripts/setup_stackforce_isaac_lab_sim_env.sh

Training Outputs And Checkpoints

Training outputs are written under:

logs/rsl_rl/<experiment_name>/<timestamp>/

Useful commands:

find logs -name "*.pt"
find logs -name "*.pt" | sort | tail -n 1
find logs -name "policy.onnx"

Training saves model_final.pt and also attempts to export exported/policies/policy.onnx.

Resume Training

python scripts/rsl_rl/train.py --task Template-2foot-Direct-v0 --resume --load_run <run_dir_name> --checkpoint <model_x.pt>

Play A Trained Policy

python scripts/rsl_rl/play.py --task Template-2foot-Direct-v0 --num_envs 1 --disable_resets

To load a specific checkpoint:

python scripts/rsl_rl/play.py --task Template-2foot-Direct-v0 --checkpoint logs/rsl_rl/<experiment_name>/<timestamp>/model_final.pt --num_envs 1 --disable_resets

Regenerate ONNX from a checkpoint:

python scripts/rsl_rl/play.py --task Template-2foot-Direct-v0 --checkpoint logs/rsl_rl/<experiment_name>/<timestamp>/model_final.pt --num_envs 1 --disable_resets --export_onnx --num_steps 1

Add A Custom Reward

Edit:

source/stackforce_simready_2foot_lab/stackforce_simready_2foot_lab/tasks/direct/2foot/custom_rewards.py

Implement your reward terms in compute_custom_reward_terms(env). Then edit:

source/stackforce_simready_2foot_lab/stackforce_simready_2foot_lab/tasks/direct/2foot/2foot_env_cfg.py

Change:

"custom_reward": 0.0

to a non-zero scale such as:

"custom_reward": 1.0

Notes:

The StackForce trimesh option is mapped to Isaac Lab rough terrain generation.
Assets stay embedded in the python package under source/stackforce_simready_2foot_lab/stackforce_simready_2foot_lab/assets.

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