Interacting with a deformable object

Interacting with a deformable object#

While deformable objects sometimes refer to a broader class of objects, such as cloths, fluids and soft bodies, Isaac Lab represents deformable objects as either surface or volume deformables. Unlike rigid objects, soft bodies can deform under external forces and collisions. In this tutorial, we focus on volume deformable bodies. For an example of surface deformables (cloth), run the deformables example.

The deformable object API and schema define/modify functions are shared across backends, while deformable property and material configuration classes are backend-specific. PhysX simulates soft bodies using the Finite Element Method (FEM); the Newton experimental backend uses the core VBD solver from isaaclab_newton.physics with the deformable object integration from isaaclab_newton.assets. The volume deformable comprises of two tetrahedral meshes – a simulation mesh and a collision mesh. The simulation mesh is used to simulate the deformations of the soft body, while the collision mesh is used to detect collisions with other objects in the scene. For PhysX-specific details, please check the PhysX documentation.

This tutorial shows how to interact with a deformable object in the simulation. We will spawn a set of soft cubes and see how to set their nodal positions and velocities, along with apply kinematic commands to the mesh nodes to move the soft body.

Note

This tutorial automatically tetrahedralizes volume deformables, and its default visualizer is Kit. Run it with the isaacsim and tetrahedralization extras:

uv run --extra isaacsim --extra tetrahedralization python scripts/tutorials/01_assets/run_deformable_object.py --visualizer kit

With the legacy installer, install the optional dependencies first:

./isaaclab.sh -i tetrahedralization

The Code#

The tutorial corresponds to the run_deformable_object.py script in the scripts/tutorials/01_assets directory.

Code for run_deformable_object.py
  1# Copyright (c) 2022-2026, The Isaac Lab Project Developers (https://github.com/isaac-sim/IsaacLab/blob/main/CONTRIBUTORS.md).
  2# All rights reserved.
  3#
  4# SPDX-License-Identifier: BSD-3-Clause
  5
  6"""
  7This script demonstrates how to work with the deformable object and interact with it.
  8
  9.. code-block:: bash
 10
 11    # Usage with default PhysX physics and default kit visualizer.
 12    uv run --extra isaacsim --extra tetrahedralization python scripts/tutorials/01_assets/run_deformable_object.py
 13
 14    # Usage with Newton VBD physics and default kit visualizer.
 15    uv run --extra isaacsim --extra tetrahedralization python scripts/tutorials/01_assets/run_deformable_object.py \
 16        --backend newton_vbd
 17
 18    # Usage with OvPhysX physics without a visualizer.
 19    uv run --extra ovphysx --extra tetrahedralization python scripts/tutorials/01_assets/run_deformable_object.py \
 20        --backend ovphysx
 21
 22"""
 23
 24"""Parse CLI first so we can decide whether to launch Isaac Sim Kit."""
 25
 26import argparse
 27from typing import TYPE_CHECKING
 28
 29from isaaclab.app import add_launcher_args, launch_simulation
 30
 31# add argparse arguments
 32parser = argparse.ArgumentParser(description="Tutorial on interacting with a deformable object.")
 33parser.add_argument(
 34    "--backend", type=str, default="physx", choices=["physx", "newton_vbd", "ovphysx"], help="Physics backend."
 35)
 36# append simulation launcher CLI arguments
 37add_launcher_args(parser)
 38# Kit cannot be combined with OvPhysX, so use no visualizer by default for that backend
 39backend_args, _ = parser.parse_known_args()
 40parser.set_defaults(visualizer=None if backend_args.backend == "ovphysx" else ["kit"])
 41# parse the arguments
 42args_cli = parser.parse_args()
 43args_cli.physics = args_cli.backend
 44
 45"""Rest everything follows."""
 46
 47import torch
 48
 49import isaaclab.sim as sim_utils
 50import isaaclab.utils.math as math_utils
 51from isaaclab.assets import AssetBaseCfg, DeformableObjectCfg
 52from isaaclab.cloner import CloneCfg
 53from isaaclab.physics import PhysicsCfg
 54from isaaclab.scene import InteractiveSceneCfg
 55from isaaclab.utils import configclass, index_fill_, instantiate
 56
 57if TYPE_CHECKING:
 58    from isaaclab.assets import DeformableObject
 59    from isaaclab.scene import InteractiveScene
 60
 61
 62youngs_modulus = 1e5
 63poissons_ratio = 0.4
 64density = 500.0
 65if args_cli.backend == "newton_vbd":
 66    from isaaclab_newton.sim.schemas import NewtonDeformableBodyPropertiesCfg
 67    from isaaclab_newton.sim.spawners.materials import NewtonDeformableBodyMaterialCfg
 68
 69    deformable_props = NewtonDeformableBodyPropertiesCfg()
 70    # Newton's VBD path skips the simulation mesh collider, so collision offsets do not apply
 71    collision_props = None
 72    physics_material = NewtonDeformableBodyMaterialCfg(
 73        k_mu=youngs_modulus / (2.0 * (1.0 + poissons_ratio)),
 74        k_lambda=youngs_modulus * poissons_ratio / ((1.0 + poissons_ratio) * (1.0 - 2.0 * poissons_ratio)),
 75        density=density,
 76    )
 77else:
 78    from isaaclab_physx.sim.schemas import PhysxCollisionCfg, PhysxDeformableBodyPropertiesCfg
 79    from isaaclab_physx.sim.spawners.materials import PhysxDeformableBodyMaterialCfg
 80
 81    deformable_props = PhysxDeformableBodyPropertiesCfg()
 82    collision_props = [PhysxCollisionCfg(rest_offset=0.0, contact_offset=0.001)]
 83    physics_material = PhysxDeformableBodyMaterialCfg(
 84        poissons_ratio=poissons_ratio, youngs_modulus=youngs_modulus, density=density
 85    )
 86
 87
 88@configclass
 89class DeformableSceneCfg(InteractiveSceneCfg):
 90    """Soft cubes on a shared ground plane."""
 91
 92    filter_collisions = False
 93    clone_cfg = CloneCfg(clone_template="/World/env_{}")
 94
 95    ground = AssetBaseCfg(prim_path="/World/defaultGroundPlane", spawn=sim_utils.GroundPlaneCfg())
 96    light = AssetBaseCfg(
 97        prim_path="/World/Light", spawn=sim_utils.DomeLightCfg(intensity=2000.0, color=(0.8, 0.8, 0.8))
 98    )
 99
100    # 3D Deformable Object
101    cube_object = DeformableObjectCfg(
102        prim_path="{ENV_REGEX_NS}/Cube",
103        spawn=sim_utils.MeshCuboidCfg(
104            size=(0.2, 0.2, 0.2),
105            deformable_props=deformable_props,
106            collision_props=collision_props,
107            visual_material=sim_utils.PreviewSurfaceCfg(diffuse_color=(0.5, 0.1, 0.0)),
108            physics_material=physics_material,
109        ),
110        init_state=DeformableObjectCfg.InitialStateCfg(pos=(0.0, 0.0, 1.0)),
111        debug_vis=True,
112    )
113
114
115def run_simulator(sim: sim_utils.SimulationContext, scene: "InteractiveScene"):
116    """Runs the simulation loop."""
117    # Extract scene entities
118    cube_object: DeformableObject = scene["cube_object"]
119
120    # Define simulation stepping
121    sim_dt = sim.get_physics_dt()
122    sim_time = 0.0
123    count = 0
124
125    # Nodal kinematic targets of the deformable bodies
126    nodal_kinematic_target = cube_object.data.nodal_kinematic_target.torch.clone()
127
128    # Simulate physics
129    while sim.is_running():
130        # reset at start and after 3 seconds
131        if count % int(3.0 / sim_dt) == 0:
132            # reset counters
133            count = 0
134
135            # reset the nodal state of the object
136            nodal_state = cube_object.data.default_nodal_state_w.torch.clone()
137            # apply random pose to the object
138            pos_w = torch.rand(cube_object.num_instances, 3, device=sim.device) * 0.1 + scene.env_origins
139            quat_w = math_utils.random_orientation(cube_object.num_instances, device=sim.device)
140            nodal_state[..., :3] = cube_object.transform_nodal_pos(nodal_state[..., :3], pos_w, quat_w)
141
142            # write nodal state to simulation
143            cube_object.write_nodal_state_to_sim_index(nodal_state)
144
145            # Write the nodal state to the kinematic target and free all vertices
146            nodal_kinematic_target[..., :3] = nodal_state[..., :3]
147            nodal_kinematic_target[..., 3] = 1.0
148            cube_object.write_nodal_kinematic_target_to_sim_index(nodal_kinematic_target)
149
150            # reset buffers
151            cube_object.reset()
152
153            print("----------------------------------------")
154            print("[INFO]: Resetting object state...")
155
156        # update the kinematic target for cubes at the positive and negative diagonal corners
157        kinematic_cubes = [1, 2]
158        # we slightly move the cube in the z-direction by picking the vertex at index 0
159        nodal_kinematic_target[kinematic_cubes, 0, 2] += 0.2 * sim_dt
160        # set vertex at index 0 to be kinematically constrained
161        # 0: constrained, 1: free
162        index_fill_(nodal_kinematic_target[:, 0, 3], kinematic_cubes, 0.0)
163        # write kinematic target to simulation
164        cube_object.write_nodal_kinematic_target_to_sim_index(nodal_kinematic_target)
165
166        # write internal data to simulation
167        cube_object.write_data_to_sim()
168        # perform step
169        sim.step()
170        # update sim-time
171        sim_time += sim_dt
172        count += 1
173        # update buffers
174        cube_object.update(sim_dt)
175
176        # print the root positions every second
177        if count % int(1.0 / sim_dt) == 0:
178            print(f"Time {sim_time:.2f}s: \tRoot position (in world): {cube_object.data.root_pos_w.torch[:, :3]}")
179
180
181def main():
182    """Main function."""
183    with launch_simulation(cfg=PhysicsCfg(), launcher_args=args_cli) as physics_cfg:
184        if args_cli.backend == "newton_vbd":
185            physics_cfg.solver_cfg.iterations = 10
186            physics_cfg.num_substeps = 4
187        sim_cfg = sim_utils.SimulationCfg(dt=0.01, device=args_cli.device, physics=physics_cfg)
188        sim = sim_utils.SimulationContext(sim_cfg)
189        # Set main camera
190        sim.set_camera_view(eye=[2.0, 2.0, 2.0], target=[0.0, 0.0, 0.75])
191        scene_cfg = DeformableSceneCfg(num_envs=4, env_spacing=0.5)
192        scene = instantiate(scene_cfg)
193        # Play the simulator
194        sim.reset()
195        # Now we are ready!
196        print("[INFO]: Setup complete...")
197        # Run the simulator
198        run_simulator(sim, scene)
199        print("[INFO]: Simulation complete...")
200
201
202if __name__ == "__main__":
203    # run the main function
204    main()

The Code Explained#

Designing the scene#

We declare the ground plane, light, and deformable cube in a subclass of scene.InteractiveSceneCfg. scene.InteractiveScene constructs the assets and handles replication internally. DeformableSceneCfg(num_envs=4, env_spacing=0.5) selects four environment origins on a centered grid with 0.5 m spacing.

In this tutorial, we create a cubical soft object using the spawn configuration similar to the deformable cube in the Spawn Objects tutorial. The only difference is that now we wrap the spawning configuration into the assets.DeformableObjectCfg class. This class contains information about the asset’s spawning strategy and default initial state. When this class is passed to the assets.DeformableObject class, it spawns the object and initializes the corresponding physics handles when the simulation is played.

Note

Deformable objects require a mesh object to be spawned with backend-specific deformable body physics properties and a matching deformable physics material. Use --backend physx for the PhysX implementation or --backend newton_vbd for the experimental Newton implementation.

The scene constructs the deformable objects from their cfg and owns their clone lifecycle. The simulation loop accesses the resulting asset through scene["cube_object"].

@configclass
class DeformableSceneCfg(InteractiveSceneCfg):
    """Soft cubes on a shared ground plane."""

    filter_collisions = False
    clone_cfg = CloneCfg(clone_template="/World/env_{}")

    ground = AssetBaseCfg(prim_path="/World/defaultGroundPlane", spawn=sim_utils.GroundPlaneCfg())
    light = AssetBaseCfg(
        prim_path="/World/Light", spawn=sim_utils.DomeLightCfg(intensity=2000.0, color=(0.8, 0.8, 0.8))
    )

    # 3D Deformable Object
    cube_object = DeformableObjectCfg(
        prim_path="{ENV_REGEX_NS}/Cube",
        spawn=sim_utils.MeshCuboidCfg(
            size=(0.2, 0.2, 0.2),
            deformable_props=deformable_props,
            collision_props=collision_props,
            visual_material=sim_utils.PreviewSurfaceCfg(diffuse_color=(0.5, 0.1, 0.0)),
            physics_material=physics_material,
        ),
        init_state=DeformableObjectCfg.InitialStateCfg(pos=(0.0, 0.0, 1.0)),
        debug_vis=True,
    )

Running the simulation loop#

Continuing from the rigid body tutorial, we reset the simulation at regular intervals, apply kinematic commands to the deformable body, step the simulation, and update the deformable object’s internal buffers.

Resetting the simulation state#

Unlike rigid bodies and articulations, deformable objects have a different state representation. The state of a deformable object is defined by the nodal positions and velocities of the mesh. The nodal positions and velocities are defined in the simulation world frame and are stored in the assets.DeformableObject.data attribute.

We use the assets.DeformableObject.data.default_nodal_state_w attribute to get the default nodal state of the spawned object prims. This default state can be configured from the assets.DeformableObjectCfg.init_state attribute, which places the cube 1 m above its environment origin in this tutorial.

Attention

The initial state in the configuration assets.DeformableObjectCfg specifies the pose of the deformable object at the time of spawning. Based on this initial state, the default nodal state is obtained when the simulation is played for the first time.

We apply transformations to the nodal positions to randomize the initial state of the deformable object.

            # reset the nodal state of the object
            nodal_state = cube_object.data.default_nodal_state_w.torch.clone()
            # apply random pose to the object
            pos_w = torch.rand(cube_object.num_instances, 3, device=sim.device) * 0.1 + scene.env_origins
            quat_w = math_utils.random_orientation(cube_object.num_instances, device=sim.device)
            nodal_state[..., :3] = cube_object.transform_nodal_pos(nodal_state[..., :3], pos_w, quat_w)

To reset the deformable object, we first set the nodal state by calling the assets.DeformableObject.write_nodal_state_to_sim() method. This method writes the nodal state of the deformable object prim into the simulation buffer. Additionally, we free all the kinematic targets set for the nodes in the previous simulation step by calling the assets.DeformableObject.write_nodal_kinematic_target_to_sim() method. We explain the kinematic targets in the next section.

Finally, we call the assets.DeformableObject.reset() method to reset any internal buffers and caches.

            # write nodal state to simulation
            cube_object.write_nodal_state_to_sim_index(nodal_state)

            # Write the nodal state to the kinematic target and free all vertices
            nodal_kinematic_target[..., :3] = nodal_state[..., :3]
            nodal_kinematic_target[..., 3] = 1.0
            cube_object.write_nodal_kinematic_target_to_sim_index(nodal_kinematic_target)

            # reset buffers
            cube_object.reset()

Stepping the simulation#

Deformable bodies support user-driven kinematic control where a user can specify position targets for some of the mesh nodes while the rest of the nodes are simulated by the active deformable solver. This partial kinematic control is useful for applications where the user wants to interact with the deformable object in a controlled manner.

In this tutorial, we apply kinematic commands to two out of the four cubes in the scene. We set the position targets for the node at index 0 (bottom-left corner) to move the cube along the z-axis.

At every step, we increment the kinematic position target for the node by a small value. Additionally, we set the flag to indicate that the target is a kinematic target for that node in the simulation buffer. These are set into the simulation buffer by calling the assets.DeformableObject.write_nodal_kinematic_target_to_sim() method.

        # update the kinematic target for cubes at the positive and negative diagonal corners
        kinematic_cubes = [1, 2]
        # we slightly move the cube in the z-direction by picking the vertex at index 0
        nodal_kinematic_target[kinematic_cubes, 0, 2] += 0.2 * sim_dt
        # set vertex at index 0 to be kinematically constrained
        # 0: constrained, 1: free
        index_fill_(nodal_kinematic_target[:, 0, 3], kinematic_cubes, 0.0)
        # write kinematic target to simulation
        cube_object.write_nodal_kinematic_target_to_sim_index(nodal_kinematic_target)

Similar to the rigid object and articulation, we perform the assets.DeformableObject.write_data_to_sim() method before stepping the simulation. For deformable objects, this method does not apply any external forces to the object. However, we keep this method for completeness and future extensions.

        # write internal data to simulation
        cube_object.write_data_to_sim()

Updating the state#

After stepping the simulation, we update the internal buffers of the deformable object prims to reflect their new state inside the assets.DeformableObject.data attribute. This is done using the assets.DeformableObject.update() method.

At a fixed interval, we print the root position of the deformable object to the terminal. As mentioned earlier, there is no concept of a root state for deformable objects. However, we compute the root position as the average position of all the nodes in the mesh.

        # update buffers
        cube_object.update(sim_dt)

        # print the root positions every second
        if count % int(1.0 / sim_dt) == 0:
            print(f"Time {sim_time:.2f}s: \tRoot position (in world): {cube_object.data.root_pos_w.torch[:, :3]}")

The Code Execution#

Now that we have gone through the code, let’s run the script and see the result:

uv run --extra isaacsim --extra tetrahedralization python scripts/tutorials/01_assets/run_deformable_object.py --visualizer kit

./isaaclab.sh -p scripts/tutorials/01_assets/run_deformable_object.py --visualizer kit

To run the same tutorial with the experimental Newton deformable backend:

uv run --extra isaacsim --extra tetrahedralization python scripts/tutorials/01_assets/run_deformable_object.py --backend newton_vbd --visualizer kit

./isaaclab.sh -p scripts/tutorials/01_assets/run_deformable_object.py --backend newton_vbd --visualizer kit

This should open a stage with a ground plane, lights, and several cubes. Two of the four cubes must be dropping from a height and settling on to the ground. Meanwhile the other two cubes must be moving along the z-axis. You should see a marker showing the kinematic target position for the nodes at the bottom-left corner of the cubes. To stop the simulation, you can either close the window, or press Ctrl+C in the terminal

result of run_deformable_object.py

This tutorial showed how to spawn deformable objects and wrap them in a DeformableObject class to initialize their physics handles which allows setting and obtaining their state. We also saw how to apply kinematic commands to the deformable object to move the mesh nodes in a controlled manner. The deformables example provides a more advanced example, including surface deformables, loading USD assets, and applying deformable materials.