Skip to main content

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 Actuators & Actions
        self.actuator_manager = ActuatorManager(
            self,
            joint_names=[".*"],
            default_pos={
                ".*_hip_joint": 0.0,
                ".*_thigh_joint": 0.8,
                ".*_calf_joint": -1.5,
            },
            kp=20,
            kv=0.5,
        )
        self.action_manager = PositionActionManager(
            self,
            scale=0.25,
            use_default_offset=True,
            actuator_manager=self.actuator_manager,
        )

        # 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}
}

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-0.5.3.tar.gz (20.4 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-0.5.3-py3-none-any.whl (88.0 kB view details)

Uploaded Python 3

File details

Details for the file genesis_forge-0.5.3.tar.gz.

File metadata

  • Download URL: genesis_forge-0.5.3.tar.gz
  • Upload date:
  • Size: 20.4 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/7.0.0 CPython/3.11.14

File hashes

Hashes for genesis_forge-0.5.3.tar.gz
Algorithm Hash digest
SHA256 364c741649f1f1f8bdd9523f5b016e15b3a02a32430b9b3ac4d4acc894e51dc3
MD5 8f0ac6222a6f8e9edfdf8d9cc29c46e1
BLAKE2b-256 4a89507134d55e583bebd51316c39bc71900a92e3fac502d2e7a1ac170bc689d

See more details on using hashes here.

File details

Details for the file genesis_forge-0.5.3-py3-none-any.whl.

File metadata

  • Download URL: genesis_forge-0.5.3-py3-none-any.whl
  • Upload date:
  • Size: 88.0 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/7.0.0 CPython/3.11.14

File hashes

Hashes for genesis_forge-0.5.3-py3-none-any.whl
Algorithm Hash digest
SHA256 7a8df0662dfc1ec442cf04f8267e17ca1326170b53df22b5beda570eb73342e7
MD5 cb244721fe81065ec6341d3018e69a69
BLAKE2b-256 18a90bde58fb59dea537dc0458b4019d9d7761eb3322c97c66e8e9b7b4d6c6ce

See more details on using hashes here.

Release history Release notifications | RSS feed

This release

0.5.3 This release

2 files

0.5.2

2 files

0.5.1

2 files

0.5.0

2 files

0.4.0

2 files

0.3.0

2 files

0.2.2

2 files

0.2.0

2 files

0.1.2

2 files

0.1.1

2 files

0.1.0

2 files

0.0.1

2 files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page