Getting Started

Prerequisites

AGILE runs on top of Isaac Lab. All Isaac Lab requirements (Isaac Sim 6.0, Python 3.12, NVIDIA GPU, etc.) apply. See the Isaac Lab installation guide. uv is used for environment and dependency management throughout.

Warning

AGILE requires Isaac Lab v3.0.0-beta2 (Isaac Sim 6.0, Python 3.12). Other versions (e.g. v2.3.2 / Isaac Sim 5.1) have incompatible APIs.

Installation

1. Install AGILE

git clone <repository-url> agile && cd agile
git lfs pull

# Install AGILE's pinned uv environment.
uv sync --frozen

# Verify public rsl-rl-lib 5.4.1 plus the AGILE patch
uv run scripts/verify_rsl_rl.py

The locked environment installs Isaac Lab v3.0.0-beta2, Isaac Sim 6.0, LEAPP, RSL-RL, and AGILE’s Python dependencies.

2. Set up pre-commit hooks (optional, for development)

./scripts/setup/setup_hooks.sh
pre-commit run --all-files  # verify

Quick Start

# Validate an environment (no trained policy needed)
uv run scripts/play.py --task Velocity-T1-v0 --num_envs 2

# Train a velocity tracking policy
uv run scripts/train.py \
    --task Velocity-T1-v0 \
    --num_envs 2048 \
    --headless \
    --logger wandb

# Evaluate a trained policy
uv run scripts/eval.py \
    --task Velocity-T1-v0 \
    --checkpoint /path/to/model.pt \
    --num_envs 32

See Training Guide for the full training guide, and Pre-trained Policies for available checkpoints and policy formats.

Project Structure

agile/
+-- agile/
|   +-- algorithms/
|   |   +-- evaluation/      # Evaluation metrics and reporting
|   +-- data/policy/         # Pre-trained checkpoints
|   +-- isaaclab_extras/     # Isaac Lab extensions
|   +-- sim2mujoco/          # Sim-to-MuJoCo transfer
|   +-- rl_env/
|       +-- assets/          # Robot USD assets
|       +-- mdp/             # MDP components (rewards, actions, observations, ...)
|       +-- tasks/           # Task definitions (self-contained configs)
|       +-- rsl_rl/          # RSL-RL integration wrappers
+-- scripts/                 # train.py, eval.py, play.py, export, setup
+-- tests/                   # Unit and E2E tests
+-- workflows/               # Docker + OSMO remote training configs
+-- run.py                   # CLI for remote OSMO training/eval
+-- third_party/rsl_rl/      # AGILE patch for public rsl-rl-lib 5.4.1