ConstructTraining / scripts /tutorials /03_envs /create_cartpole_base_env.py
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# Copyright (c) 2022-2026, The Isaac Lab Project Developers (https://github.com/isaac-sim/IsaacLab/blob/main/CONTRIBUTORS.md).
# All rights reserved.
#
# SPDX-License-Identifier: BSD-3-Clause
"""
This script demonstrates how to create a simple environment with a cartpole. It combines the concepts of
scene, action, observation and event managers to create an environment.
.. code-block:: bash
./isaaclab.sh -p scripts/tutorials/03_envs/create_cartpole_base_env.py --num_envs 32
"""
"""Launch Isaac Sim Simulator first."""
import argparse
from isaaclab.app import AppLauncher
# add argparse arguments
parser = argparse.ArgumentParser(description="Tutorial on creating a cartpole base environment.")
parser.add_argument("--num_envs", type=int, default=16, help="Number of environments to spawn.")
# append AppLauncher cli args
AppLauncher.add_app_launcher_args(parser)
# parse the arguments
args_cli = parser.parse_args()
# launch omniverse app
app_launcher = AppLauncher(args_cli)
simulation_app = app_launcher.app
"""Rest everything follows."""
import math
import torch
import isaaclab.envs.mdp as mdp
from isaaclab.envs import ManagerBasedEnv, ManagerBasedEnvCfg
from isaaclab.managers import EventTermCfg as EventTerm
from isaaclab.managers import ObservationGroupCfg as ObsGroup
from isaaclab.managers import ObservationTermCfg as ObsTerm
from isaaclab.managers import SceneEntityCfg
from isaaclab.utils import configclass
from isaaclab_tasks.manager_based.classic.cartpole.cartpole_env_cfg import CartpoleSceneCfg
@configclass
class ActionsCfg:
"""Action specifications for the environment."""
joint_efforts = mdp.JointEffortActionCfg(asset_name="robot", joint_names=["slider_to_cart"], scale=5.0)
@configclass
class ObservationsCfg:
"""Observation specifications for the environment."""
@configclass
class PolicyCfg(ObsGroup):
"""Observations for policy group."""
# observation terms (order preserved)
joint_pos_rel = ObsTerm(func=mdp.joint_pos_rel)
joint_vel_rel = ObsTerm(func=mdp.joint_vel_rel)
def __post_init__(self) -> None:
self.enable_corruption = False
self.concatenate_terms = True
# observation groups
policy: PolicyCfg = PolicyCfg()
@configclass
class EventCfg:
"""Configuration for events."""
# on startup
add_pole_mass = EventTerm(
func=mdp.randomize_rigid_body_mass,
mode="startup",
params={
"asset_cfg": SceneEntityCfg("robot", body_names=["pole"]),
"mass_distribution_params": (0.1, 0.5),
"operation": "add",
},
)
# on reset
reset_cart_position = EventTerm(
func=mdp.reset_joints_by_offset,
mode="reset",
params={
"asset_cfg": SceneEntityCfg("robot", joint_names=["slider_to_cart"]),
"position_range": (-1.0, 1.0),
"velocity_range": (-0.1, 0.1),
},
)
reset_pole_position = EventTerm(
func=mdp.reset_joints_by_offset,
mode="reset",
params={
"asset_cfg": SceneEntityCfg("robot", joint_names=["cart_to_pole"]),
"position_range": (-0.125 * math.pi, 0.125 * math.pi),
"velocity_range": (-0.01 * math.pi, 0.01 * math.pi),
},
)
@configclass
class CartpoleEnvCfg(ManagerBasedEnvCfg):
"""Configuration for the cartpole environment."""
# Scene settings
scene = CartpoleSceneCfg(num_envs=1024, env_spacing=2.5)
# Basic settings
observations = ObservationsCfg()
actions = ActionsCfg()
events = EventCfg()
def __post_init__(self):
"""Post initialization."""
# viewer settings
self.viewer.eye = [4.5, 0.0, 6.0]
self.viewer.lookat = [0.0, 0.0, 2.0]
# step settings
self.decimation = 4 # env step every 4 sim steps: 200Hz / 4 = 50Hz
# simulation settings
self.sim.dt = 0.005 # sim step every 5ms: 200Hz
def main():
"""Main function."""
# parse the arguments
env_cfg = CartpoleEnvCfg()
env_cfg.scene.num_envs = args_cli.num_envs
env_cfg.sim.device = args_cli.device
# setup base environment
env = ManagerBasedEnv(cfg=env_cfg)
# simulate physics
count = 0
while simulation_app.is_running():
with torch.inference_mode():
# reset
if count % 300 == 0:
count = 0
env.reset()
print("-" * 80)
print("[INFO]: Resetting environment...")
# sample random actions
joint_efforts = torch.randn_like(env.action_manager.action)
# step the environment
obs, _ = env.step(joint_efforts)
# print current orientation of pole
print("[Env 0]: Pole joint: ", obs["policy"][0][1].item())
# update counter
count += 1
# close the environment
env.close()
if __name__ == "__main__":
# run the main function
main()
# close sim app
simulation_app.close()