> This page is for version Release 3.0 (default). > For other versions, use one of these documentation indexes: > - Release 3.0 (default): https://docs.nvidia.com/isaaclab/3.0/llms.txt > - Release 2.3: https://docs.nvidia.com/isaaclab/2.3/llms.txt > - Release 2.2: https://docs.nvidia.com/isaaclab/2.2/llms.txt > - Release 2.1: https://docs.nvidia.com/isaaclab/2.1/llms.txt > For clean Markdown of any page, append .md to the page URL. > For a complete documentation index, see https://docs.nvidia.com/isaaclab/llms.txt. > For AI client integration (Claude Code, Cursor, etc.), connect to the MCP server at https://docs.nvidia.com/isaaclab/_mcp/server. # Robot and articulation configuration A jointed robot is represented as an articulation in Isaac Lab. This guide covers reusing an existing robot configuration and authoring a new `~assets.ArticulationCfg`. The `~assets.ArticulationCfg` is a configuration object that defines the properties of an `~assets.Articulation` in Isaac Lab. > **Note** > > While we only cover the creation of an `~assets.ArticulationCfg` in this guide, > the process is similar for creating any other asset configuration object. ## Reusing a robot configuration Maintained robot configurations live in `source/isaaclab_assets/isaaclab_assets/robots`. Import a configuration from `isaaclab_assets` and copy it before changing its spawn properties, initial state, or actuators. Keep project-specific configurations in a Python module in your own project; they do not need to be added to Isaac Lab. Import `clone` and `replace` from `isaaclab.utils`. For example, `robot_cfg = clone(CARTPOLE_CFG)` creates an independent configuration. Use `replace(robot_cfg, prim_path="{ENV_REGEX_NS}/Robot")` when adding it to an `~scene.InteractiveSceneCfg`. The physics backend is selected separately from this robot configuration, as explained below. We will use the Cartpole example to demonstrate how to create an `~assets.ArticulationCfg`. The Cartpole is a simple robot that consists of a cart with a pole attached to it. The cart is free to move along a rail, and the pole is free to rotate about the cart. The file for this configuration example is `source/isaaclab_assets/isaaclab_assets/robots/cartpole.py`. ```python # 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 """Configuration for a simple Cartpole robot.""" from isaaclab_newton.sim.schemas import NewtonArticulationCfg from isaaclab_physx.sim.schemas import PhysxArticulationCfg, PhysxRigidBodyCfg import isaaclab.sim as sim_utils from isaaclab.actuators import ImplicitActuatorCfg from isaaclab.assets import ArticulationCfg from isaaclab.utils.assets import ISAACLAB_NUCLEUS_DIR ## # Configuration ## CARTPOLE_CFG = ArticulationCfg( spawn=sim_utils.UsdFileCfg( usd_path=f"{ISAACLAB_NUCLEUS_DIR}/Robots/Classic/Cartpole/cartpole.usd", rigid_props=[ sim_utils.UsdPhysicsRigidBodyCfg(rigid_body_enabled=True), PhysxRigidBodyCfg( max_linear_velocity=1000.0, max_angular_velocity=1000.0, max_depenetration_velocity=100.0, enable_gyroscopic_forces=True, ), ], articulation_props=[ PhysxArticulationCfg( enabled_self_collisions=False, solver_position_iteration_count=4, solver_velocity_iteration_count=0, sleep_threshold=0.005, stabilization_threshold=0.001, ), NewtonArticulationCfg(self_collision_enabled=False), ], ), init_state=ArticulationCfg.InitialStateCfg( pos=(0.0, 0.0, 2.0), joint_pos={"slider_to_cart": 0.0, "cart_to_pole": 0.0} ), actuators={ "cart_actuator": ImplicitActuatorCfg( joint_names_expr=["slider_to_cart"], joint_effort_limit=400.0, stiffness=0.0, damping=10.0, ), "pole_actuator": ImplicitActuatorCfg( joint_names_expr=["cart_to_pole"], joint_effort_limit=400.0, stiffness=0.0, damping=0.0 ), }, ) """Configuration for a simple Cartpole robot.""" ``` ## Choosing shared and backend-specific settings Use the shared `~assets.ArticulationCfg` for the robot's initial state and actuators. The simulation selects the physics backend separately. For common USD properties, use classes from `isaaclab.sim.schemas`, such as `~sim.schemas.RigidBodyBaseCfg` and `~sim.schemas.ArticulationRootBaseCfg`. Use `isaaclab_physx.sim.schemas.Physx*Cfg` for PhysX tuning and `isaaclab_newton.sim.schemas.Newton*Cfg` / `Mujoco*Cfg` for Newton and MJWarp-specific settings. The [Schema Configuration Classes](/source/concepts/schema_cfgs) guide explains the available classes and their USD namespaces; [../concepts/schema_fragments](/source/concepts/schema_fragments) shows how to author both backends' attributes in one spawn configuration. The Cartpole below uses the compatibility names `RigidBodyPropertiesCfg` and `ArticulationRootPropertiesCfg`. Its PhysX solver iterations and sleep thresholds do not configure Newton's solver. When adapting it to Newton, retain the shared initial-state and actuator configuration and configure the Newton solver separately. For example, to override Newton's self-collision setting: ```python from isaaclab_assets import CARTPOLE_CFG from isaaclab_newton.sim.schemas import NewtonArticulationRootPropertiesCfg from isaaclab.utils import clone robot_cfg = clone(CARTPOLE_CFG) robot_cfg.spawn.articulation_props = NewtonArticulationRootPropertiesCfg(self_collision_enabled=False) ``` See [solver_tuning_mjwarp](/source/how-to/solver_tuning_mjwarp) for solver settings, [prepare_asset_for_newton](/source/how-to/prepare_asset_for_newton) for asset tuning, and [Multi-backend assets](/source/how-to/import_new_asset#multi-backend-assets) for converted USD variants. ## Defining the spawn configuration As explained in [Spawning prims into the scene](/source/how-to/spawn_prims) tutorials, the spawn configuration defines the properties of the assets to be spawned. This spawning may happen procedurally, or through an existing asset file (e.g. USD or URDF). In this example, we will spawn the Cartpole from a USD file. When spawning an asset from a USD file, we define its `~sim.spawners.from_files.UsdFileCfg`. This configuration object takes in the following parameters: * `~sim.spawners.from_files.UsdFileCfg.usd_path`: The USD file path to spawn from * `~sim.spawners.from_files.UsdFileCfg.rigid_props`: The properties of the articulation's rigid-body links * `~sim.spawners.from_files.UsdFileCfg.articulation_props`: The properties of the articulation root The last two parameters are optional. If not specified, they are kept at their default values in the USD file. ```python spawn=sim_utils.UsdFileCfg( usd_path=f"{ISAACLAB_NUCLEUS_DIR}/Robots/Classic/Cartpole/cartpole.usd", rigid_props=[ sim_utils.UsdPhysicsRigidBodyCfg(rigid_body_enabled=True), PhysxRigidBodyCfg( max_linear_velocity=1000.0, max_angular_velocity=1000.0, max_depenetration_velocity=100.0, enable_gyroscopic_forces=True, ), ], articulation_props=[ PhysxArticulationCfg( enabled_self_collisions=False, solver_position_iteration_count=4, solver_velocity_iteration_count=0, sleep_threshold=0.005, stabilization_threshold=0.001, ), NewtonArticulationCfg(self_collision_enabled=False), ], ), ``` To import articulation from a URDF file instead of a USD file, you can replace the `~sim.spawners.from_files.UsdFileCfg` with a `~sim.spawners.from_files.UrdfFileCfg`. For more details, please check the API documentation. ## Defining the initial state Every asset requires defining their initial or *default* state in the simulation through its configuration. This configuration is stored into the asset's default state buffers that can be accessed when the asset's state needs to be reset. > **Note** > > The initial state of an asset is defined w\.r.t. its local environment frame. This then needs to > be transformed into the global simulation frame when resetting the asset's state. For more > details, please check the [Interacting with an articulation](/source/how-to/run_articulation) tutorial. For an articulation, the `~assets.ArticulationCfg.InitialStateCfg` object defines the initial state of the root of the articulation and the initial state of all its joints. In this example, we will spawn the Cartpole at the origin of the XY plane at a Z height of 2.0 meters. Meanwhile, the joint positions and velocities are set to 0.0. ```python init_state=ArticulationCfg.InitialStateCfg( pos=(0.0, 0.0, 2.0), joint_pos={"slider_to_cart": 0.0, "cart_to_pole": 0.0} ), ``` ## Defining the actuator configuration Actuators are a crucial component of an articulation. Through this configuration, it is possible to define the type of actuator model to use. We can use the internal actuator model provided by the physics engine (i.e. the implicit actuator model), or use a custom actuator model which is governed by a user-defined system of equations (i.e. the explicit actuator model). For more details on actuators, see [Actuators](/source/concepts/actuators). The cartpole's articulation has two actuators, one corresponding to its each joint: `cart_to_pole` and `slider_to_cart`. We use two different actuator models for these actuators as an example. However, since they are both using the same actuator model, it is possible to combine them into a single actuator model. ```python actuators={ "cart_actuator": ImplicitActuatorCfg( joint_names_expr=["slider_to_cart"], joint_effort_limit=400.0, stiffness=0.0, damping=10.0, ), "pole_actuator": ImplicitActuatorCfg( joint_names_expr=["cart_to_pole"], joint_effort_limit=400.0, stiffness=0.0, damping=0.0 ), }, ``` ```python actuators={ "all_joints": ImplicitActuatorCfg( joint_names_expr=[".*"], joint_effort_limit=400.0, joint_velocity_limit=100.0, stiffness={"slider_to_cart": 0.0, "cart_to_pole": 0.0}, damping={"slider_to_cart": 10.0, "cart_to_pole": 0.0}, ), }, ``` > **Note** > > Newton resolves the target mode of joints configured with > `~isaaclab.actuators.ImplicitActuatorCfg` before solver construction: > stiffness-only selects position mode, damping-only velocity mode, both gains > combined position/velocity mode, and zero gains effort mode. A gain of > `None` retains the imported USD value; explicit actuator configurations use > effort mode. Zero-gain USD drives therefore need no placeholder solely for a > configured actuator. See [Importing a New Asset](/source/how-to/import_new_asset) for when > `isaaclab.sim.schemas.JointDrivePropertiesCfg.ensure_drives_exist` > remains useful. ## ActuatorCfg velocity/effort limits considerations Use the following fields in an actuator configuration. They select joints and are resolved when the articulation is constructed; the canonical runtime values live on `~isaaclab.assets.ArticulationData`. See [Joint and actuator property ownership](/source/concepts/actuators#joint-and-actuator-property-ownership) for the ownership model and runtime mutation paths. | Field | Implicit actuator | Explicit actuator | | ------------------------- | --------------------------------------------------------------------- | ---------------------------------------------------------------------------------------- | | `joint_effort_limit` | Writes the solver drive effort limit. | Writes the solver effort limit; defaults high to avoid a second model clip. | | `actuator_effort_limit` | Not supported. | Clips actuator-model output. | | `joint_velocity_limit` | Requests a solver velocity constraint. | Requests a solver velocity constraint. | | `actuator_velocity_limit` | Creates the soft velocity-limit snapshot; it is not a solver request. | Describes the actuator rated speed; speed-dependent models use it in their torque curve. | | `effort_limit` | Deprecated alias for `joint_effort_limit`. | Deprecated alias for `actuator_effort_limit`. | | `velocity_limit` | Deprecated alias for `actuator_velocity_limit`. | Deprecated alias for `actuator_velocity_limit`. | Solver velocity enforcement is backend-dependent. `joint_velocity_limit` records the requested joint state but is not a backend-independent safety clamp; see [Validate actuators and limits](/source/how-to/prepare_asset_for_newton#validate-actuators-and-limits). ## USD vs. ActuatorCfg discrepancy resolution USD having default value and the fact that ActuatorCfg can be specified with None, or a overriding value can sometime be confusing what exactly gets written into simulation. The resolution follows these simple rules,per joint and per property: | **Condition** | **ActuatorCfg Value** | **Applied** | | -------------------- | --------------------- | ------------------- | | No override provided | Not Specified | USD Value | | Override provided | User's ActuatorCfg | Same as ActuatorCfg | Digging into USD can sometime be unconvinent, to help clarify what exact value is written, we designed a flag `isaaclab.assets.ArticulationCfg.actuator_value_resolution_debug_print`, to help user figure out what exact value gets used in simulation. Whenever an actuator parameter is overridden in the user's ActuatorCfg (or left unspecified), we compare it to the value read from the USD definition and record any differences. For each joint and each property, if unmatching value is found, we log the resolution: 1. **USD Value** The default limit or gain parsed from the USD asset. 2. **ActuatorCfg Value** The user-provided override (or “Not Specified” if none was given). 3. **Applied** The final value actually used for simulation: if the user didn't override it, this matches the USD value; otherwise it reflects the user's setting. This resolution info is emitted as a warning table only when discrepancies exist. Here's an example of what you'll see: | Group | Property | Name | ID | USD Value | ActuatorCfg Value | Applied | | -------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ----------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | panda_shoulder panda_forearm panda_hand | joint_velocity_limit stiffness damping armature joint_velocity_limit stiffness damping armature friction joint_velocity_limit stiffness armature friction | panda_joint1 panda_joint2 panda_joint3 panda_joint4 panda_joint1 panda_joint2 panda_joint3 panda_joint4 panda_joint1 panda_joint2 panda_joint3 panda_joint4 panda_joint1 panda_joint2 panda_joint3 panda_joint4 panda_joint5 panda_joint6 panda_joint7 panda_joint5 panda_joint6 panda_joint7 panda_joint5 panda_joint6 panda_joint7 panda_joint5 panda_joint6 panda_joint7 panda_joint5 panda_joint6 panda_joint7 panda_finger_joint1 panda_finger_joint2 panda_finger_joint1 panda_finger_joint2 panda_finger_joint1 panda_finger_joint2 panda_finger_joint1 panda_finger_joint2 | 0 1 2 3 0 1 2 3 0 1 2 3 0 1 2 3 4 5 6 4 5 6 4 5 6 4 5 6 4 5 6 7 8 7 8 7 8 7 8 | 2.17e+00 2.17e+00 2.17e+00 2.17e+00 2.29e+04 2.29e+04 2.29e+04 2.29e+04 4.58e+03 4.58e+03 4.58e+03 4.58e+03 0.00e+00 0.00e+00 0.00e+00 0.00e+00 2.61e+00 2.61e+00 2.61e+00 2.29e+04 2.29e+04 2.29e+04 4.58e+03 4.58e+03 4.58e+03 0.00e+00 0.00e+00 0.00e+00 0.00e+00 0.00e+00 0.00e+00 2.00e-01 2.00e-01 1.00e+06 1.00e+06 0.00e+00 0.00e+00 0.00e+00 0.00e+00 | Not Specified Not Specified Not Specified Not Specified 8.00e+01 8.00e+01 8.00e+01 8.00e+01 4.00e+00 4.00e+00 4.00e+00 4.00e+00 Not Specified Not Specified Not Specified Not Specified Not Specified Not Specified Not Specified 8.00e+01 8.00e+01 8.00e+01 4.00e+00 4.00e+00 4.00e+00 Not Specified Not Specified Not Specified Not Specified Not Specified Not Specified Not Specified Not Specified 2.00e+03 2.00e+03 Not Specified Not Specified Not Specified Not Specified | 2.17e+00 2.17e+00 2.17e+00 2.17e+00 8.00e+01 8.00e+01 8.00e+01 8.00e+01 4.00e+00 4.00e+00 4.00e+00 4.00e+00 0.00e+00 0.00e+00 0.00e+00 0.00e+00 2.61e+00 2.61e+00 2.61e+00 8.00e+01 8.00e+01 8.00e+01 4.00e+00 4.00e+00 4.00e+00 0.00e+00 0.00e+00 0.00e+00 0.00e+00 0.00e+00 0.00e+00 2.00e-01 2.00e-01 2.00e+03 2.00e+03 0.00e+00 0.00e+00 0.00e+00 0.00e+00 | To keep the cleaniness of logging, `isaaclab.assets.ArticulationCfg.actuator_value_resolution_debug_print` default to False, remember to turn it on when wishes. ## Example: configure and run two robots The runnable example `scripts/tutorials/01_assets/add_new_robot.py` contrasts a minimal Jetbot configuration with a more detailed Dofbot configuration. Start with an imported USD asset (see [import_new_asset](/source/how-to/import_new_asset)) and define its spawn properties and actuators. Jetbot retains the joint gains authored in the USD by setting stiffness and damping to `None`. Both fields must be specified, even when using these USD defaults: ```python JETBOT_CONFIG = ArticulationCfg( spawn=sim_utils.UsdFileCfg(usd_path=f"{ISAAC_NUCLEUS_DIR}/Robots/NVIDIA/Jetbot/jetbot.usd"), actuators={"wheel_acts": ImplicitActuatorCfg(joint_names_expr=[".*"], damping=None, stiffness=None)}, ) ``` Dofbot additionally sets initial joint positions, groups joints by name, and specifies actuator gains and limits. Its solver iterations and maximum depenetration velocity are PhysX-specific; use [Choosing shared and backend-specific settings](/source/how-to/write_articulation_cfg#choosing-shared-and-backend-specific-settings) when adapting these properties to Newton. The keys in `init_state.joint_pos` identify USD joints, not actuator groups. Joint names can be matched with regular expressions; for example, `.*` selects all joints. ```python DOFBOT_CONFIG = ArticulationCfg( spawn=sim_utils.UsdFileCfg( usd_path=f"{ISAAC_NUCLEUS_DIR}/Robots/Yahboom/Dofbot/dofbot.usd", rigid_props=PhysxRigidBodyCfg( disable_gravity=False, max_depenetration_velocity=5.0, ), articulation_props=[ PhysxArticulationCfg( enabled_self_collisions=True, solver_position_iteration_count=8, solver_velocity_iteration_count=0 ), NewtonArticulationCfg(self_collision_enabled=True), ], ), init_state=ArticulationCfg.InitialStateCfg( joint_pos={ "joint1": 0.0, "joint2": 0.0, "joint3": 0.0, "joint4": 0.0, }, pos=(0.25, -0.25, 0.0), ), actuators={ "front_joints": ImplicitActuatorCfg( joint_names_expr=["joint[1-2]"], joint_effort_limit=100.0, joint_velocity_limit=100.0, stiffness=10000.0, damping=100.0, ), "joint3_act": ImplicitActuatorCfg( joint_names_expr=["joint3"], joint_effort_limit=100.0, joint_velocity_limit=100.0, stiffness=10000.0, damping=100.0, ), "joint4_act": ImplicitActuatorCfg( joint_names_expr=["joint4"], joint_effort_limit=100.0, joint_velocity_limit=100.0, stiffness=10000.0, damping=100.0, ), }, ) ``` The example adds both configurations to an `InteractiveSceneCfg`, assigns each robot a path under every environment, and constructs the scene. Its loop resets root and joint states, sets joint targets, writes commands, steps physics, and updates the scene buffers. See [Using the Interactive Scene](/source/how-to/create_scene) for scene construction and [Interacting with an articulation](/source/how-to/run_articulation) for the reset and control loop. ```python # 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 import argparse from typing import TYPE_CHECKING from isaaclab.app import add_launcher_args, launch_simulation from isaaclab.utils import instantiate, replace # add argparse arguments parser = argparse.ArgumentParser( description="This script demonstrates adding a custom robot to an Isaac Lab environment." ) parser.add_argument("--num_envs", type=int, default=1, help="Number of environments to spawn.") # append simulation launcher cli args add_launcher_args(parser) # parse the arguments args_cli = parser.parse_args() import numpy as np import torch from isaaclab_newton.sim.schemas import NewtonArticulationCfg from isaaclab_physx.sim.schemas import PhysxArticulationCfg, PhysxRigidBodyCfg import isaaclab.sim as sim_utils from isaaclab.actuators import ImplicitActuatorCfg from isaaclab.assets import AssetBaseCfg from isaaclab.assets.articulation import ArticulationCfg from isaaclab.scene import InteractiveSceneCfg from isaaclab.utils.assets import ISAAC_NUCLEUS_DIR if TYPE_CHECKING: from isaaclab.scene import InteractiveScene JETBOT_CONFIG = ArticulationCfg( spawn=sim_utils.UsdFileCfg(usd_path=f"{ISAAC_NUCLEUS_DIR}/Robots/NVIDIA/Jetbot/jetbot.usd"), actuators={"wheel_acts": ImplicitActuatorCfg(joint_names_expr=[".*"], damping=None, stiffness=None)}, ) DOFBOT_CONFIG = ArticulationCfg( spawn=sim_utils.UsdFileCfg( usd_path=f"{ISAAC_NUCLEUS_DIR}/Robots/Yahboom/Dofbot/dofbot.usd", rigid_props=PhysxRigidBodyCfg( disable_gravity=False, max_depenetration_velocity=5.0, ), articulation_props=[ PhysxArticulationCfg( enabled_self_collisions=True, solver_position_iteration_count=8, solver_velocity_iteration_count=0 ), NewtonArticulationCfg(self_collision_enabled=True), ], ), init_state=ArticulationCfg.InitialStateCfg( joint_pos={ "joint1": 0.0, "joint2": 0.0, "joint3": 0.0, "joint4": 0.0, }, pos=(0.25, -0.25, 0.0), ), actuators={ "front_joints": ImplicitActuatorCfg( joint_names_expr=["joint[1-2]"], joint_effort_limit=100.0, joint_velocity_limit=100.0, stiffness=10000.0, damping=100.0, ), "joint3_act": ImplicitActuatorCfg( joint_names_expr=["joint3"], joint_effort_limit=100.0, joint_velocity_limit=100.0, stiffness=10000.0, damping=100.0, ), "joint4_act": ImplicitActuatorCfg( joint_names_expr=["joint4"], joint_effort_limit=100.0, joint_velocity_limit=100.0, stiffness=10000.0, damping=100.0, ), }, ) class NewRobotsSceneCfg(InteractiveSceneCfg): """Designs the scene.""" # Ground-plane ground = AssetBaseCfg(prim_path="/World/defaultGroundPlane", spawn=sim_utils.GroundPlaneCfg()) # lights dome_light = AssetBaseCfg( prim_path="/World/Light", spawn=sim_utils.DomeLightCfg(intensity=3000.0, color=(0.75, 0.75, 0.75)) ) # robot Jetbot = replace(JETBOT_CONFIG, prim_path="{ENV_REGEX_NS}/Jetbot") Dofbot = replace(DOFBOT_CONFIG, prim_path="{ENV_REGEX_NS}/Dofbot") def run_simulator(sim: sim_utils.SimulationContext, scene: "InteractiveScene"): sim_dt = sim.get_physics_dt() sim_time = 0.0 count = 0 # wheel-velocity templates allocated once on the simulation device; the joint # target setters dispatch to GPU Warp kernels and reject CPU tensors. straight_action = torch.tensor([[10.0, 10.0]], device=sim.device).repeat(scene.num_envs, 1) turn_action = torch.tensor([[5.0, -5.0]], device=sim.device).repeat(scene.num_envs, 1) while sim.is_running(): # reset if count % 500 == 0: # reset counters count = 0 # reset the scene entities to their initial positions offset by the environment origins root_jetbot_pose = scene["Jetbot"].data.default_root_pose.torch.clone() root_jetbot_pose[:, :3] += scene.env_origins root_dofbot_pose = scene["Dofbot"].data.default_root_pose.torch.clone() root_dofbot_pose[:, :3] += scene.env_origins # copy the default root state to the sim for the jetbot's orientation and velocity scene["Jetbot"].write_root_pose_to_sim_index(root_pose=root_jetbot_pose) root_jetbot_vel = scene["Jetbot"].data.default_root_vel.torch.clone() scene["Jetbot"].write_root_velocity_to_sim_index(root_velocity=root_jetbot_vel) scene["Dofbot"].write_root_pose_to_sim_index(root_pose=root_dofbot_pose) root_dofbot_vel = scene["Dofbot"].data.default_root_vel.torch.clone() scene["Dofbot"].write_root_velocity_to_sim_index(root_velocity=root_dofbot_vel) # copy the default joint states to the sim joint_pos, joint_vel = ( scene["Jetbot"].data.default_joint_pos.torch.clone(), scene["Jetbot"].data.default_joint_vel.torch.clone(), ) scene["Jetbot"].write_joint_position_to_sim_index(position=joint_pos) scene["Jetbot"].write_joint_velocity_to_sim_index(velocity=joint_vel) joint_pos, joint_vel = ( scene["Dofbot"].data.default_joint_pos.torch.clone(), scene["Dofbot"].data.default_joint_vel.torch.clone(), ) scene["Dofbot"].write_joint_position_to_sim_index(position=joint_pos) scene["Dofbot"].write_joint_velocity_to_sim_index(velocity=joint_vel) # clear internal buffers scene.reset() print("[INFO]: Resetting Jetbot and Dofbot state...") # drive around if count % 100 < 75: # Drive straight by setting equal wheel velocities action = straight_action else: # Turn by applying different velocities action = turn_action scene["Jetbot"].set_joint_velocity_target_index(target=action) # wave wave_action = scene["Dofbot"].data.default_joint_pos.torch.clone() wave_action[:, 0:4] = 0.25 * np.sin(2 * np.pi * 0.5 * sim_time) scene["Dofbot"].set_joint_position_target_index(target=wave_action) scene.write_data_to_sim() sim.step() sim_time += sim_dt count += 1 scene.update(sim_dt) def main(): """Main function.""" # Configure the simulation sim_cfg = sim_utils.SimulationCfg(device=args_cli.device) # Launch the simulator runtime that the configuration needs with launch_simulation(sim_cfg, args_cli): # Initialize the simulation context sim = sim_utils.SimulationContext(sim_cfg) sim.set_camera_view([3.5, 0.0, 3.2], [0.0, 0.0, 0.5]) # Design scene scene_cfg = NewRobotsSceneCfg(num_envs=args_cli.num_envs, env_spacing=2.0) scene = instantiate(scene_cfg) # Play the simulator sim.reset() # Now we are ready! print("[INFO]: Setup complete...") # Run the simulator run_simulator(sim, scene) if __name__ == "__main__": main() ``` Run the example in the Isaac Sim viewport: ```bash uv run isaaclab -p scripts/tutorials/01_assets/add_new_robot.py --viz kit ``` This example uses PhysX physics and requires Isaac Sim. The Dofbot gripper is not actuated in this example, so a warning about unconfigured joints is expected. Stop the example with `Ctrl+C`. ![Jetbot and Dofbot running in the example scene.](/isaaclab/_fern-img/b4151a90385b3292fa455cb62ef0b1137de3e88a0cf22d62967793599b0ac50c.webp)