Isaac Lab Locomotion Learning

This repository provides a simple framework for training robots using CPGRBF networks with PIBB.

Installation

Tested: Ubuntu 22.04, IsaacSim 5.1, IsaacLab 2.3.0

• Install Isaac Lab by following the installation guide. We recommend using the conda installation as it simplifies calling Python scripts from the terminal.

• Clone this repository separately from the Isaac Lab installation (i.e. outside the IsaacLab directory):

git clone https://github.com/worasuch/IsaacLab-LocoNets.git

• Using a python interpreter that has Isaac Lab installed, install the library

cd IsaacLab-LocoNets
python -m pip install -e source/IsaacLabLocoNets

• Verify that the extension is correctly installed by running the following command:

python scripts/ES/train.py --task Slalom --headless --num_envs 2

Training

Train with default configuration (as defined in the config file)

python scripts/ES/train.py --task <TASK_NAME>

Customize training parameters via CLI (without modifying the config file)

python scripts/ES/train.py --task Slalom --num_envs 1024 --cpg_rbf --headless --wandb

Playing

Path to collect the model is following

• logs/es/TASK_NAME/MODEL/EXPERIMENT/ model /CHECKPOINT
• models path are in
  • logs/es/Slalom/cpg_rbf/2026-04-16_21-42-33/model/model_499.pickle

python scripts/ES/play.py --cpg_rbf --task Slalom --num_envs 1 --experiment 2026-04-16_21-42-33 --checkpoint model_499.pickle

Logging

• To log training progress, we use wandb for real-time visualization. Before running any experiments, make sure you’re logged in by executing:

wandb login