Skip to main content

A robotics RL training frameworks for Genesis inspired by Isaac Lab and Gymnasium.

Project description

Genesis Forge

Genesis Forge is a powerful robotics reinforcement learning framework using the Genesis physics simulator. It provides a flexible and modular architecture to get your robot up and running quickly with less boilerplate work.

RL Robotics What?

Today, modern robots learn to balance, walk, and manipulate objects using Reinforcement Learning algorithms. You simply create a program that defines a task and provides feedback on the robot's performance — much like training a dog with treats and commands. But with modern GPUs, you can parallelize this process across thousands of simulated robots at a time. Genesis Forge is a framework that makes this very easy to do, with documentation and examples to get you started.

Features:

  • 🦿 Action manager - Control your joints and actuators, within limits and with domain randomization
  • 🏆 Reward/Termination managers - Simple and extensible reward/termination handling with automatic logging
  • ↪️ Command managers - Commands your robot with debug visualization
  • 🏔️ Terrain manager - Helpful terrain utilities and curriculums
  • 💥 Contact manager - Comprehensive contact/collision detection and reward/termination functions
  • 🎬 Video Wrapper - Automatically records videos at regular intervals during training
  • 🕹️ Gamepad interface - Control trained policies directly with a physical gamepad controller.
  • And more...

Learn more in the documentation

Massively parallel locomotion training Gamepad controller interface Rough terrain Complex robots

Install

Before installing Genesis Forge, ensure you have:

  • Python >=3.10,<3.14
  • pip package manager

(Optional) CUDA-compatible GPU for faster training

pip install genesis-forge

Example

Here's an example of a environment to teach the Go2 robot how to follow direction commands. See the full runnable example here.

class Go2CEnv(ManagedEnvironment):
    def __init__(self, num_envs: int = 1):
        super().__init__(num_envs=num_envs)

        # Construct the scene
        self.scene = gs.Scene(show_viewer=False)
        self.scene.add_entity(gs.morphs.Plane())
        self.robot = self.scene.add_entity(
            gs.morphs.URDF(
                file="urdf/go2/urdf/go2.urdf",
                pos=[0.0, 0.0, 0.35],
                quat=[1.0, 0.0, 0.0, 0.0],
            ),
        )

    def config(self):
        # Robot manager - Reset the robot's initial position on reset
        self.robot_manager = EntityManager(
            self,
            entity_attr="robot",
            on_reset={
                "position": {
                    "fn": reset.position,
                    "params": {
                        "position": [0.0, 0.0, 0.35],
                        "quat": [1.0, 0.0, 0.0, 0.0],
                    },
                },
            },
        )

        # Joint Actions
        self.action_manager = PositionActionManager(
            self,
            joint_names=[".*"],
            default_pos={
                ".*_hip_joint": 0.0,
                ".*_thigh_joint": 0.8,
                ".*_calf_joint": -1.5,
            },
            scale=0.25,
            use_default_offset=True,
            pd_kp=20,
            pd_kv=0.5,
        )

        # Commanded direction
        self.velocity_command = VelocityCommandManager(
            self,
            range={
                "lin_vel_x": [-1.0, 1.0],
                "lin_vel_y": [-1.0, 1.0],
                "ang_vel_z": [-1.0, 1.0],
            },
        )

        # Rewards
        RewardManager(
            self,
            cfg={
                "base_height_target": {
                    "weight": -50.0,
                    "fn": rewards.base_height,
                    "params": {
                        "target_height": 0.3,
                    },
                },
                "tracking_lin_vel": {
                    "weight": 1.0,
                    "fn": rewards.command_tracking_lin_vel,
                    "params": {
                        "vel_cmd_manager": self.velocity_command,
                    },
                },
                "tracking_ang_vel": {
                    "weight": 1.0,
                    "fn": rewards.command_tracking_ang_vel,
                    "params": {
                        "vel_cmd_manager": self.velocity_command,
                    },
                },
                "lin_vel_z": {
                    "weight": -1.0,
                    "fn": rewards.lin_vel_z_l2,
                },
            },
        )

        # Termination conditions
        self.termination_manager = TerminationManager(
            self,
            logging_enabled=True,
            term_cfg={
                # The episode ended
                "timeout": {
                    "fn": terminations.timeout,
                    "time_out": True,
                },
                # Terminate if the robot's pitch and yaw angles are too large
                "fall_over": {
                    "fn": terminations.bad_orientation,
                    "params": {
                        "limit_angle": 10, # degrees
                    },
                },
            },
        )

        # Observations
        ObservationManager(
            self,
            cfg={
                "velocity_cmd": { "fn": self.velocity_command.observation },
                "angle_velocity": {
                    "fn": lambda env: self.robot_manager.get_angular_velocity(),
                },
                "linear_velocity": {
                    "fn": lambda env: self.robot_manager.get_linear_velocity(),
                },
                "projected_gravity": {
                    "fn": lambda env: self.robot_manager.get_projected_gravity(),
                },
                "dof_position": {
                    "fn": lambda env: self.action_manager.get_dofs_position(),
                },
                "dof_velocity": {
                    "fn": lambda env: self.action_manager.get_dofs_velocity(),
                    "scale": 0.05,
                },
                "actions": {
                    "fn": lambda env: self.action_manager.get_actions(),
                },
            },
        )

Learn More

Check out the user guide and API reference

Citation

If you used Genesis Forge in your research, we would appreciate it if you could cite it.

@misc{Genesis-Forge,
  author = {Jeremy Gillick},
  title = {Genesis Forge: A modular framework for RL robot environments},
  month = {September},
  year = {2025},
  url = {https://github.com/jgillick/genesis-forge}
}

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

genesis_forge-0.2.2.tar.gz (30.4 MB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

genesis_forge-0.2.2-py3-none-any.whl (73.2 kB view details)

Uploaded Python 3

File details

Details for the file genesis_forge-0.2.2.tar.gz.

File metadata

  • Download URL: genesis_forge-0.2.2.tar.gz
  • Upload date:
  • Size: 30.4 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.11.9

File hashes

Hashes for genesis_forge-0.2.2.tar.gz
Algorithm Hash digest
SHA256 f317ec0e5a0227eae1843101022832a7e5d6f580b8dab13bd52122023460a568
MD5 8a014eb18631321cd3916082c557833d
BLAKE2b-256 55578834b52b67fef0368dc36ebc15614d3250ff3b6af5afe9409f1b8d409f57

See more details on using hashes here.

File details

Details for the file genesis_forge-0.2.2-py3-none-any.whl.

File metadata

  • Download URL: genesis_forge-0.2.2-py3-none-any.whl
  • Upload date:
  • Size: 73.2 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.11.9

File hashes

Hashes for genesis_forge-0.2.2-py3-none-any.whl
Algorithm Hash digest
SHA256 b3f21d4d550c3a68ba313d8ee1008e1b5dbff436e226c45f86cf1c65a231f59c
MD5 4368c45054664248aee06b2505aeab77
BLAKE2b-256 2ed4f4bfb4a21d83f4b692bf5dad8b58e2a5e7f2afd8bfdfdd7753fccb476cbd

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page