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Isaac LabHow-to guide

Spawning Multiple Assets

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Typical spawning configurations (introduced in the Spawning prims into the scene tutorial) copy one asset across all prim paths resolved from an expression. Multi-asset workflows cover two related composition needs:

  1. A rigid object collection batches several rigid objects in every environment behind one data and command API.
  2. A multi-asset spawner declares several variants for one scene asset binding, allowing environments to contain different geometry or robot variants.

This guide demonstrates both mechanisms and explains how their execution differs between PhysX and Newton.

The packaged multi-asset example provides the reference script, multi_asset.py.

# 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
"""Spawn several asset types across cloned environments.
.. code-block:: bash
uvx isaaclab example multi-asset --num_envs 1024
"""
from __future__ import annotations
import argparse
from typing import TYPE_CHECKING
from isaaclab.app import add_launcher_args, launch_simulation
parser = argparse.ArgumentParser(
description="Example of spawning different objects in multiple environments.",
conflict_handler="resolve",
)
parser.add_argument("--num_envs", type=int, default=512, help="Number of environments to spawn.")
parser.add_argument(
"--physics", default="newton_mjwarp", choices=["isaacsim_physx", "newton_mjwarp"], help="Physics backend."
)
parser.add_argument("--max_steps", type=int, default=-1, help="Stop after this many steps; negative runs forever.")
add_launcher_args(parser)
parser.set_defaults(visualizer=["newton_gl"])
args_cli = parser.parse_args()
if args_cli.max_steps == 0 or args_cli.max_steps < -1:
parser.error("--max_steps must be positive or -1.")
from isaaclab_newton.sim.schemas import NewtonArticulationCfg
from isaaclab_physx.sim.schemas import PhysxArticulationCfg, PhysxRigidBodyCfg
import isaaclab.sim as sim_utils
from isaaclab.assets import ArticulationCfg, AssetBaseCfg, RigidObjectCfg, RigidObjectCollectionCfg
from isaaclab.physics import PhysicsCfg
from isaaclab.scene import InteractiveSceneCfg
from isaaclab_assets.robots.anymal import ANYDRIVE_3_LSTM_ACTUATOR_CFG # isort: skip
from isaaclab.utils import Timer, configclass, instantiate
from isaaclab.utils.assets import ISAACLAB_NUCLEUS_DIR
if TYPE_CHECKING:
from isaaclab.assets import Articulation, RigidObject, RigidObjectCollection
from isaaclab.scene import InteractiveScene
# Visual material presets for the multi-asset variants.
GREEN_MATERIAL = {"visual_material": sim_utils.PreviewSurfaceCfg(diffuse_color=(0.0, 1.0, 0.0), metallic=0.2)}
RED_MATERIAL = {"visual_material": sim_utils.PreviewSurfaceCfg(diffuse_color=(1.0, 0.0, 0.0), metallic=0.2)}
BLUE_MATERIAL = {"visual_material": sim_utils.PreviewSurfaceCfg(diffuse_color=(0.0, 0.0, 1.0), metallic=0.2)}
GOLD_MATERIAL = {"visual_material": sim_utils.PreviewSurfaceCfg(diffuse_color=(1.0, 0.75, 0.0), metallic=0.2)}
PURPLE_MATERIAL = {"visual_material": sim_utils.PreviewSurfaceCfg(diffuse_color=(0.5, 0.0, 1.0), metallic=0.2)}
OBJECT_PHYSICS = {
"rigid_props": PhysxRigidBodyCfg(solver_position_iteration_count=4, solver_velocity_iteration_count=0),
"mass_props": sim_utils.MassCfg(mass=1.0),
"collision_props": sim_utils.UsdPhysicsCollisionCfg(),
}
##
# Scene Configuration
##
@configclass
class MultiObjectSceneCfg(InteractiveSceneCfg):
"""Configuration for a multi-object 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))
)
# rigid object
object: RigidObjectCfg = RigidObjectCfg(
prim_path="/World/envs/env_.*/Object",
spawn=sim_utils.MultiAssetSpawnerCfg(
assets_cfg=[
sim_utils.CylinderCfg(radius=0.3, height=0.6, **GREEN_MATERIAL),
sim_utils.CuboidCfg(size=(0.3, 0.3, 0.3), **RED_MATERIAL),
sim_utils.SphereCfg(radius=0.3, **BLUE_MATERIAL),
sim_utils.CylinderCfg(radius=0.3, height=0.6, **GOLD_MATERIAL),
sim_utils.CuboidCfg(size=(0.3, 0.3, 0.3), **GOLD_MATERIAL),
sim_utils.SphereCfg(radius=0.3, **GOLD_MATERIAL),
sim_utils.CylinderCfg(radius=0.3, height=0.6, **PURPLE_MATERIAL),
sim_utils.CuboidCfg(size=(0.3, 0.3, 0.3), **PURPLE_MATERIAL),
sim_utils.SphereCfg(radius=0.3, **PURPLE_MATERIAL),
],
random_choice=False,
**OBJECT_PHYSICS,
),
init_state=RigidObjectCfg.InitialStateCfg(pos=(0.0, 0.0, 2.0)),
)
# object collection
object_collection: RigidObjectCollectionCfg = RigidObjectCollectionCfg(
rigid_objects={
"object_A": RigidObjectCfg(
prim_path="/World/envs/env_.*/Object_A",
spawn=sim_utils.SphereCfg(radius=0.1, **RED_MATERIAL, **OBJECT_PHYSICS),
init_state=RigidObjectCfg.InitialStateCfg(pos=(0.0, -0.5, 2.0)),
),
"object_B": RigidObjectCfg(
prim_path="/World/envs/env_.*/Object_B",
spawn=sim_utils.CuboidCfg(size=(0.1, 0.1, 0.1), **RED_MATERIAL, **OBJECT_PHYSICS),
init_state=RigidObjectCfg.InitialStateCfg(pos=(0.0, 0.5, 2.0)),
),
"object_C": RigidObjectCfg(
prim_path="/World/envs/env_.*/Object_C",
spawn=sim_utils.CylinderCfg(radius=0.1, height=0.3, **RED_MATERIAL, **OBJECT_PHYSICS),
init_state=RigidObjectCfg.InitialStateCfg(pos=(0.5, 0.0, 2.0)),
),
}
)
# articulation
robot: ArticulationCfg = ArticulationCfg(
prim_path="/World/envs/env_.*/Robot",
spawn=sim_utils.MultiUsdFileCfg(
usd_path=[
f"{ISAACLAB_NUCLEUS_DIR}/Robots/ANYbotics/ANYmal-C/anymal_c.usd",
f"{ISAACLAB_NUCLEUS_DIR}/Robots/ANYbotics/ANYmal-D/anymal_d.usd",
],
random_choice=False,
rigid_props=PhysxRigidBodyCfg(
disable_gravity=False,
retain_accelerations=False,
linear_damping=0.0,
angular_damping=0.0,
max_linear_velocity=1000.0,
max_angular_velocity=1000.0,
max_depenetration_velocity=1.0,
),
articulation_props=[
PhysxArticulationCfg(
enabled_self_collisions=True, solver_position_iteration_count=4, solver_velocity_iteration_count=0
),
NewtonArticulationCfg(self_collision_enabled=True),
],
activate_contact_sensors=True,
),
init_state=ArticulationCfg.InitialStateCfg(
pos=(0.0, 0.0, 0.6),
joint_pos={
".*HAA": 0.0, # all HAA
".*F_HFE": 0.4, # both front HFE
".*H_HFE": -0.4, # both hind HFE
".*F_KFE": -0.8, # both front KFE
".*H_KFE": 0.8, # both hind KFE
},
),
actuators={"legs": ANYDRIVE_3_LSTM_ACTUATOR_CFG},
)
##
# Simulation Loop
##
def run_simulator(sim: sim_utils.SimulationContext, scene: InteractiveScene):
"""Runs the simulation loop."""
# Extract scene entities
# note: we only do this here for readability.
rigid_object: RigidObject = scene["object"]
rigid_object_collection: RigidObjectCollection = scene["object_collection"]
robot: Articulation = scene["robot"]
# Define simulation stepping
sim_dt = sim.get_physics_dt()
count = 0
step_count = 0
# Step while a visualizer window is still open (or none exist, e.g. headless); works for kit and newton.
while sim.is_running() and (args_cli.max_steps < 0 or step_count < args_cli.max_steps):
# Reset
if count % 250 == 0:
# reset counter
count = 0
# reset the scene entities
# object
root_pose = rigid_object.data.default_root_pose.torch.clone()
root_pose[:, :3] += scene.env_origins
rigid_object.write_root_pose_to_sim_index(root_pose=root_pose)
root_vel = rigid_object.data.default_root_vel.torch.clone()
rigid_object.write_root_velocity_to_sim_index(root_velocity=root_vel)
# object collection
default_pose_w = rigid_object_collection.data.default_body_pose.torch.clone()
default_pose_w[..., :3] += scene.env_origins.unsqueeze(1)
rigid_object_collection.write_body_pose_to_sim_index(body_poses=default_pose_w)
default_vel_w = rigid_object_collection.data.default_body_vel.torch.clone()
rigid_object_collection.write_body_com_velocity_to_sim_index(body_velocities=default_vel_w)
# robot
# -- root state
root_pose = robot.data.default_root_pose.torch.clone()
root_pose[:, :3] += scene.env_origins
robot.write_root_pose_to_sim_index(root_pose=root_pose)
root_vel = robot.data.default_root_vel.torch
robot.write_root_velocity_to_sim_index(root_velocity=root_vel)
# -- joint state
joint_pos = robot.data.default_joint_pos.torch
joint_vel = robot.data.default_joint_vel.torch
robot.write_joint_position_to_sim_index(position=joint_pos)
robot.write_joint_velocity_to_sim_index(velocity=joint_vel)
# clear internal buffers
scene.reset()
print("[INFO]: Resetting scene state...")
# Apply action to robot
robot.set_joint_position_target_index(target=robot.data.default_joint_pos.torch)
# Write data to sim
scene.write_data_to_sim()
# Perform step
sim.step()
step_count += 1
# Increment counter
count += 1
# Update buffers
scene.update(sim_dt)
def main():
"""Main function."""
with launch_simulation(cfg=PhysicsCfg(), launcher_args=args_cli) as physics_cfg:
sim_cfg = sim_utils.SimulationCfg(dt=0.005, device=args_cli.device, physics=physics_cfg)
sim = sim_utils.SimulationContext(sim_cfg)
# Set main camera
sim.set_camera_view([2.5, 0.0, 4.0], [0.0, 0.0, 2.0])
# Design scene
scene_cfg = MultiObjectSceneCfg(num_envs=args_cli.num_envs, env_spacing=2.0, replicate_physics=True)
if args_cli.physics == "newton_mjwarp":
# Newton views currently require a uniform body layout across worlds.
scene_cfg.object.spawn.assets_cfg = scene_cfg.object.spawn.assets_cfg[1:2]
scene_cfg.robot.spawn.usd_path = scene_cfg.robot.spawn.usd_path[0]
with Timer("[INFO] Time to create scene: "):
scene = instantiate(scene_cfg)
sim.reset()
print("[INFO]: Setup complete...")
run_simulator(sim, scene)
if __name__ == "__main__":
main()

With the default Newton configuration, this script creates multiple environments containing:

  • a rigid object collection containing a sphere, a cube, and a cylinder
  • a rigid object selected from nine geometry and material variants by the clone plan
  • an articulation selected from the ANYmal-C and ANYmal-D variants by the clone plan

Rigid object collections

Use a rigid object collection when every environment contains the same set of independently moving rigid bodies and you want to access them as one batch. The collection exposes data with an (env, object, ...) layout and accepts (env_ids, obj_ids) selections for commands. Compared with managing each object separately, the collection uses one batched physics view.

object_collection: RigidObjectCollectionCfg = RigidObjectCollectionCfg(
rigid_objects={
"object_A": RigidObjectCfg(
prim_path="/World/envs/env_.*/Object_A",
spawn=sim_utils.SphereCfg(radius=0.1, **RED_MATERIAL, **OBJECT_PHYSICS),
init_state=RigidObjectCfg.InitialStateCfg(pos=(0.0, -0.5, 2.0)),
),
"object_B": RigidObjectCfg(
prim_path="/World/envs/env_.*/Object_B",
spawn=sim_utils.CuboidCfg(size=(0.1, 0.1, 0.1), **RED_MATERIAL, **OBJECT_PHYSICS),
init_state=RigidObjectCfg.InitialStateCfg(pos=(0.0, 0.5, 2.0)),
),
"object_C": RigidObjectCfg(
prim_path="/World/envs/env_.*/Object_C",
spawn=sim_utils.CylinderCfg(radius=0.1, height=0.3, **RED_MATERIAL, **OBJECT_PHYSICS),
init_state=RigidObjectCfg.InitialStateCfg(pos=(0.5, 0.0, 2.0)),
),
}
)

The RigidObjectCollectionCfg configuration owns a dictionary of RigidObjectCfg instances. Each dictionary key is the object’s stable identifier within the collection.

The example resets all collection members through the same API used by both physics backends:

default_pose_w = rigid_object_collection.data.default_body_pose.torch.clone()
default_pose_w[..., :3] += scene.env_origins.unsqueeze(1)
rigid_object_collection.write_body_pose_to_sim_index(body_poses=default_pose_w)
default_vel_w = rigid_object_collection.data.default_body_vel.torch.clone()
rigid_object_collection.write_body_com_velocity_to_sim_index(body_velocities=default_vel_w)

Spawning variants for one scene asset

Use MultiAssetSpawnerCfg and MultiUsdFileCfg to declare the available variants for one scene asset binding. InteractiveScene includes these variants in its clone plan and assigns one valid prototype combination to each environment.

For configuration-based assets, assign MultiAssetSpawnerCfg to the RigidObjectCfg spawn configuration:

object: RigidObjectCfg = RigidObjectCfg(
prim_path="/World/envs/env_.*/Object",
spawn=sim_utils.MultiAssetSpawnerCfg(
assets_cfg=[
sim_utils.CylinderCfg(radius=0.3, height=0.6, **GREEN_MATERIAL),
sim_utils.CuboidCfg(size=(0.3, 0.3, 0.3), **RED_MATERIAL),
sim_utils.SphereCfg(radius=0.3, **BLUE_MATERIAL),
sim_utils.CylinderCfg(radius=0.3, height=0.6, **GOLD_MATERIAL),
sim_utils.CuboidCfg(size=(0.3, 0.3, 0.3), **GOLD_MATERIAL),
sim_utils.SphereCfg(radius=0.3, **GOLD_MATERIAL),
sim_utils.CylinderCfg(radius=0.3, height=0.6, **PURPLE_MATERIAL),
sim_utils.CuboidCfg(size=(0.3, 0.3, 0.3), **PURPLE_MATERIAL),
sim_utils.SphereCfg(radius=0.3, **PURPLE_MATERIAL),
],
random_choice=False,
**OBJECT_PHYSICS,
),
init_state=RigidObjectCfg.InitialStateCfg(pos=(0.0, 0.0, 2.0)),
)

The assets_cfg list defines the prototypes available to the clone plan. Variant assignment is controlled by clone_strategy; the default sequential strategy assigns combinations in round-robin order. To sample combinations randomly instead, set the strategy before constructing the scene:

from isaaclab import cloner
scene_cfg.clone_cfg.clone_strategy = cloner.random

For USD assets, assign MultiUsdFileCfg to the ArticulationCfg spawn configuration:

robot: ArticulationCfg = ArticulationCfg(
prim_path="/World/envs/env_.*/Robot",
spawn=sim_utils.MultiUsdFileCfg(
usd_path=[
f"{ISAACLAB_NUCLEUS_DIR}/Robots/ANYbotics/ANYmal-C/anymal_c.usd",
f"{ISAACLAB_NUCLEUS_DIR}/Robots/ANYbotics/ANYmal-D/anymal_d.usd",
],
random_choice=False,
rigid_props=PhysxRigidBodyCfg(
disable_gravity=False,
retain_accelerations=False,
linear_damping=0.0,
angular_damping=0.0,
max_linear_velocity=1000.0,
max_angular_velocity=1000.0,
max_depenetration_velocity=1.0,
),
articulation_props=[
PhysxArticulationCfg(
enabled_self_collisions=True, solver_position_iteration_count=4, solver_velocity_iteration_count=0
),
NewtonArticulationCfg(self_collision_enabled=True),
],
activate_contact_sensors=True,
),
init_state=ArticulationCfg.InitialStateCfg(
pos=(0.0, 0.0, 0.6),
joint_pos={
".*HAA": 0.0, # all HAA
".*F_HFE": 0.4, # both front HFE
".*H_HFE": -0.4, # both hind HFE
".*F_KFE": -0.8, # both front KFE
".*H_KFE": 0.8, # both hind KFE
},
),
actuators={"legs": ANYDRIVE_3_LSTM_ACTUATOR_CFG},
)

Variant compatibility

All variants behind one batched asset interface must have a compatible structure. Articulation variants must have the same links, joints, collision-body count, and names. Rigid object variants can differ in geometry and material while retaining a compatible rigid-body layout. Model structurally different assets as separate scene bindings.

Clone planning and physics replication

InteractiveScene represents multi-asset variants as clone-plan prototypes. It can therefore keep replicate_physics enabled and replicate each prototype only to its assigned environments. Do not disable physics replication merely because a scene uses a multi-asset spawner. Reserve replicate_physics=False for per-environment stage differences that cannot be represented as clone variants; that mode is not supported by the Newton backend.

The example keeps physics replication enabled. For Newton, it also narrows the standalone object and articulation to one variant because their batched Newton views currently require a uniform body layout across worlds:

scene_cfg = MultiObjectSceneCfg(num_envs=args_cli.num_envs, env_spacing=2.0, replicate_physics=True)
if args_cli.physics == "newton_mjwarp":
# Newton views currently require a uniform body layout across worlds.
scene_cfg.object.spawn.assets_cfg = scene_cfg.object.spawn.assets_cfg[1:2]
scene_cfg.robot.spawn.usd_path = scene_cfg.robot.spawn.usd_path[0]

For more detail on prototype assignment and replication, see cloning.

Run the example

The physics backend and visualizer are selected independently. Run one of these commands from the repository root:

uv run --extra isaacsim isaaclab example multi-asset \
--physics isaacsim_physx --visualizer kit --num_envs 2048

The Newton commands exercise the same RigidObjectCollectionCfg and (env_ids, obj_ids) APIs as the PhysX command. They do not demonstrate per-environment object or articulation variants because of the uniform-layout restriction described above; use the PhysX command to inspect that part of the example. See the installation guide before running the kitless command.

To stop the simulation, you can close the window, or press Ctrl+C in the terminal.