# Launching PPO Policy Training for 'v1' Across 4096 Environments
# This command initiates the PPO algorithm-based training for the humanoid task.
python scripts/train.py --task=hector --run_name v1 --headless --num_envs 4096
# Evaluating the Trained PPO Policy 'v1'
# This command loads the 'v1' policy for performance assessment in its environment.
# Additionally, it automatically exports a JIT model, suitable for deployment purposes.
python scripts/play.py --task=hector --run_name v1
The implementation of this repo relies on resources from humanoid_gym and legged_gym and rsl_rl projects, created by the Robotic Systems Lab. We specifically utilize the LeggedRobot and humanoid implementations from their research to enhance our codebase.