# 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 work with the deformable object and interact with it. .. code-block:: bash # Usage ./isaaclab.sh -p scripts/tutorials/01_assets/run_deformable_object.py """ """Launch Isaac Sim Simulator first.""" import argparse from isaaclab.app import AppLauncher # add argparse arguments parser = argparse.ArgumentParser(description="Tutorial on interacting with a deformable object.") # 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 torch import isaaclab.sim as sim_utils import isaaclab.utils.math as math_utils from isaaclab.assets import DeformableObject, DeformableObjectCfg from isaaclab.sim import SimulationContext def design_scene(): """Designs the scene.""" # Ground-plane cfg = sim_utils.GroundPlaneCfg() cfg.func("/World/defaultGroundPlane", cfg) # Lights cfg = sim_utils.DomeLightCfg(intensity=2000.0, color=(0.8, 0.8, 0.8)) cfg.func("/World/Light", cfg) # Create separate groups called "Origin1", "Origin2", "Origin3" # Each group will have a robot in it origins = [[0.25, 0.25, 0.0], [-0.25, 0.25, 0.0], [0.25, -0.25, 0.0], [-0.25, -0.25, 0.0]] for i, origin in enumerate(origins): sim_utils.create_prim(f"/World/Origin{i}", "Xform", translation=origin) # Deformable Object cfg = DeformableObjectCfg( prim_path="/World/Origin.*/Cube", spawn=sim_utils.MeshCuboidCfg( size=(0.2, 0.2, 0.2), deformable_props=sim_utils.DeformableBodyPropertiesCfg(rest_offset=0.0, contact_offset=0.001), visual_material=sim_utils.PreviewSurfaceCfg(diffuse_color=(0.5, 0.1, 0.0)), physics_material=sim_utils.DeformableBodyMaterialCfg(poissons_ratio=0.4, youngs_modulus=1e5), ), init_state=DeformableObjectCfg.InitialStateCfg(pos=(0.0, 0.0, 1.0)), debug_vis=True, ) cube_object = DeformableObject(cfg=cfg) # return the scene information scene_entities = {"cube_object": cube_object} return scene_entities, origins def run_simulator(sim: sim_utils.SimulationContext, entities: dict[str, DeformableObject], origins: torch.Tensor): """Runs the simulation loop.""" # Extract scene entities # note: we only do this here for readability. In general, it is better to access the entities directly from # the dictionary. This dictionary is replaced by the InteractiveScene class in the next tutorial. cube_object = entities["cube_object"] # Define simulation stepping sim_dt = sim.get_physics_dt() sim_time = 0.0 count = 0 # Nodal kinematic targets of the deformable bodies nodal_kinematic_target = cube_object.data.nodal_kinematic_target.clone() # Simulate physics while simulation_app.is_running(): # reset if count % 250 == 0: # reset counters sim_time = 0.0 count = 0 # reset the nodal state of the object nodal_state = cube_object.data.default_nodal_state_w.clone() # apply random pose to the object pos_w = torch.rand(cube_object.num_instances, 3, device=sim.device) * 0.1 + 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) # write nodal state to simulation cube_object.write_nodal_state_to_sim(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(nodal_kinematic_target) # reset buffers cube_object.reset() print("----------------------------------------") print("[INFO]: Resetting object state...") # update the kinematic target for cubes at index 0 and 3 # we slightly move the cube in the z-direction by picking the vertex at index 0 nodal_kinematic_target[[0, 3], 0, 2] += 0.001 # set vertex at index 0 to be kinematically constrained # 0: constrained, 1: free nodal_kinematic_target[[0, 3], 0, 3] = 0.0 # write kinematic target to simulation cube_object.write_nodal_kinematic_target_to_sim(nodal_kinematic_target) # write internal data to simulation cube_object.write_data_to_sim() # perform step sim.step() # update sim-time sim_time += sim_dt count += 1 # update buffers cube_object.update(sim_dt) # print the root position if count % 50 == 0: print(f"Root position (in world): {cube_object.data.root_pos_w[:, :3]}") def main(): """Main function.""" # Load kit helper sim_cfg = sim_utils.SimulationCfg(device=args_cli.device) sim = SimulationContext(sim_cfg) # Set main camera sim.set_camera_view(eye=[3.0, 0.0, 1.0], target=[0.0, 0.0, 0.5]) # Design scene scene_entities, scene_origins = design_scene() scene_origins = torch.tensor(scene_origins, device=sim.device) # Play the simulator sim.reset() # Now we are ready! print("[INFO]: Setup complete...") # Run the simulator run_simulator(sim, scene_entities, scene_origins) if __name__ == "__main__": # run the main function main() # close sim app simulation_app.close()