Source code for omni.isaac.lab.assets.rigid_object_collection.rigid_object_collection

# Copyright (c) 2022-2024, The Isaac Lab Project Developers.
# All rights reserved.
#
# SPDX-License-Identifier: BSD-3-Clause

from __future__ import annotations

import re
import torch
import weakref
from collections.abc import Sequence
from typing import TYPE_CHECKING

import omni.kit.app
import omni.log
import omni.physics.tensors.impl.api as physx
import omni.timeline
from pxr import UsdPhysics

import omni.isaac.lab.sim as sim_utils
import omni.isaac.lab.utils.math as math_utils
import omni.isaac.lab.utils.string as string_utils

from ..asset_base import AssetBase
from .rigid_object_collection_data import RigidObjectCollectionData

if TYPE_CHECKING:
    from .rigid_object_collection_cfg import RigidObjectCollectionCfg


[docs]class RigidObjectCollection(AssetBase): """A rigid object collection class. This class represents a collection of rigid objects in the simulation, where the state of the rigid objects can be accessed and modified using a batched ``(env_ids, object_ids)`` API. For each rigid body in the collection, the root prim of the asset must have the `USD RigidBodyAPI`_ applied to it. This API is used to define the simulation properties of the rigid bodies. On playing the simulation, the physics engine will automatically register the rigid bodies and create a corresponding rigid body handle. This handle can be accessed using the :attr:`root_physx_view` attribute. .. note:: Rigid objects in the collection are uniquely identified via the key of the dictionary :attr:`~omni.isaac.lab.assets.RigidObjectCollectionCfg.rigid_objects` in :class:`~omni.isaac.lab.assets.RigidObjectCollectionCfg`. This differs from the class :class:`~omni.isaac.lab.assets.RigidObject`, where a rigid object is identified by the name of the Xform where the `USD RigidBodyAPI`_ is applied. This would not be possible for the rigid object collection since the :attr:`~omni.isaac.lab.assets.RigidObjectCollectionCfg.rigid_objects` dictionary could contain the same rigid object multiple times, leading to ambiguity. .. _`USD RigidBodyAPI`: https://openusd.org/dev/api/class_usd_physics_rigid_body_a_p_i.html """ cfg: RigidObjectCollectionCfg """Configuration instance for the rigid object collection."""
[docs] def __init__(self, cfg: RigidObjectCollectionCfg): """Initialize the rigid object collection. Args: cfg: A configuration instance. """ # check that the config is valid cfg.validate() # store inputs self.cfg = cfg # flag for whether the asset is initialized self._is_initialized = False for rigid_object_cfg in self.cfg.rigid_objects.values(): # check if the rigid object path is valid # note: currently the spawner does not work if there is a regex pattern in the leaf # For example, if the prim path is "/World/Object_[1,2]" since the spawner will not # know which prim to spawn. This is a limitation of the spawner and not the asset. asset_path = rigid_object_cfg.prim_path.split("/")[-1] asset_path_is_regex = re.match(r"^[a-zA-Z0-9/_]+$", asset_path) is None # spawn the asset if rigid_object_cfg.spawn is not None and not asset_path_is_regex: rigid_object_cfg.spawn.func( rigid_object_cfg.prim_path, rigid_object_cfg.spawn, translation=rigid_object_cfg.init_state.pos, orientation=rigid_object_cfg.init_state.rot, ) # check that spawn was successful matching_prims = sim_utils.find_matching_prims(rigid_object_cfg.prim_path) if len(matching_prims) == 0: raise RuntimeError(f"Could not find prim with path {rigid_object_cfg.prim_path}.") # stores object names self._object_names_list = [] # note: Use weakref on all callbacks to ensure that this object can be deleted when its destructor is called. # add callbacks for stage play/stop # The order is set to 10 which is arbitrary but should be lower priority than the default order of 0 timeline_event_stream = omni.timeline.get_timeline_interface().get_timeline_event_stream() self._initialize_handle = timeline_event_stream.create_subscription_to_pop_by_type( int(omni.timeline.TimelineEventType.PLAY), lambda event, obj=weakref.proxy(self): obj._initialize_callback(event), order=10, ) self._invalidate_initialize_handle = timeline_event_stream.create_subscription_to_pop_by_type( int(omni.timeline.TimelineEventType.STOP), lambda event, obj=weakref.proxy(self): obj._invalidate_initialize_callback(event), order=10, ) self._debug_vis_handle = None self._root_state_dep_warn = False self._root_pose_dep_warn = False self._root_vel_dep_warn = False
""" Properties """ @property def data(self) -> RigidObjectCollectionData: return self._data @property def num_instances(self) -> int: """Number of instances of the collection.""" return self.root_physx_view.count // self.num_objects @property def num_objects(self) -> int: """Number of objects in the collection. This corresponds to the distinct number of rigid bodies in the collection. """ return len(self.object_names) @property def object_names(self) -> list[str]: """Ordered names of objects in the rigid object collection.""" return self._object_names_list @property def root_physx_view(self) -> physx.RigidBodyView: """Rigid body view for the rigid body collection (PhysX). Note: Use this view with caution. It requires handling of tensors in a specific way. """ return self._root_physx_view """ Operations. """
[docs] def reset(self, env_ids: torch.Tensor | None = None, object_ids: slice | torch.Tensor | None = None): """Resets all internal buffers of selected environments and objects. Args: env_ids: The indices of the object to reset. Defaults to None (all instances). object_ids: The indices of the object to reset. Defaults to None (all objects). """ # resolve all indices if env_ids is None: env_ids = self._ALL_ENV_INDICES if object_ids is None: object_ids = self._ALL_OBJ_INDICES # reset external wrench self._external_force_b[env_ids[:, None], object_ids] = 0.0 self._external_torque_b[env_ids[:, None], object_ids] = 0.0
[docs] def write_data_to_sim(self): """Write external wrench to the simulation. Note: We write external wrench to the simulation here since this function is called before the simulation step. This ensures that the external wrench is applied at every simulation step. """ # write external wrench if self.has_external_wrench: self.root_physx_view.apply_forces_and_torques_at_position( force_data=self.reshape_data_to_view(self._external_force_b), torque_data=self.reshape_data_to_view(self._external_torque_b), position_data=None, indices=self._env_obj_ids_to_view_ids(self._ALL_ENV_INDICES, self._ALL_OBJ_INDICES), is_global=False, )
[docs] def update(self, dt: float): self._data.update(dt)
""" Operations - Finders. """
[docs] def find_objects( self, name_keys: str | Sequence[str], preserve_order: bool = False ) -> tuple[torch.Tensor, list[str]]: """Find objects in the collection based on the name keys. Please check the :meth:`omni.isaac.lab.utils.string_utils.resolve_matching_names` function for more information on the name matching. Args: name_keys: A regular expression or a list of regular expressions to match the object names. preserve_order: Whether to preserve the order of the name keys in the output. Defaults to False. Returns: A tuple containing the object indices and names. """ obj_ids, obj_names = string_utils.resolve_matching_names(name_keys, self.object_names, preserve_order) return torch.tensor(obj_ids, device=self.device), obj_names
""" Operations - Write to simulation. """
[docs] def write_object_state_to_sim( self, object_state: torch.Tensor, env_ids: torch.Tensor | None = None, object_ids: slice | torch.Tensor | None = None, ): """Set the object state over selected environment and object indices into the simulation. The object state comprises of the cartesian position, quaternion orientation in (w, x, y, z), and linear and angular velocity. All the quantities are in the simulation frame. Args: object_state: Object state in simulation frame. Shape is (len(env_ids), len(object_ids), 13). env_ids: Environment indices. If None, then all indices are used. object_ids: Object indices. If None, then all indices are used. """ # deprecation warning if not self._root_state_dep_warn: omni.log.warn( "DeprecationWarning: RigidObjectCollection.write_object_state_to_sim will be removed in a future" " release. Please use write_object_link_state_to_sim or write_object_com_state_to_sim instead." ) self._root_state_dep_warn = True # set into simulation self.write_object_pose_to_sim(object_state[..., :7], env_ids=env_ids, object_ids=object_ids) self.write_object_velocity_to_sim(object_state[..., 7:], env_ids=env_ids, object_ids=object_ids)
[docs] def write_object_com_state_to_sim( self, object_state: torch.Tensor, env_ids: torch.Tensor | None = None, object_ids: slice | torch.Tensor | None = None, ): """Set the object center of mass state over selected environment indices into the simulation. The object state comprises of the cartesian position, quaternion orientation in (w, x, y, z), and linear and angular velocity. All the quantities are in the simulation frame. Args: object_state: Object state in simulation frame. Shape is (len(env_ids), len(object_ids), 13). env_ids: Environment indices. If None, then all indices are used. object_ids: Object indices. If None, then all indices are used. """ # set into simulation self.write_object_com_pose_to_sim(object_state[..., :7], env_ids=env_ids, object_ids=object_ids) self.write_object_com_velocity_to_sim(object_state[..., 7:], env_ids=env_ids, object_ids=object_ids)
[docs] def write_object_pose_to_sim( self, object_pose: torch.Tensor, env_ids: torch.Tensor | None = None, object_ids: slice | torch.Tensor | None = None, ): """Set the object pose over selected environment and object indices into the simulation. The object pose comprises of the cartesian position and quaternion orientation in (w, x, y, z). Args: object_pose: Object poses in simulation frame. Shape is (len(env_ids), len(object_ids), 7). env_ids: Environment indices. If None, then all indices are used. object_ids: Object indices. If None, then all indices are used. """ # deprecation warning if not self._root_pose_dep_warn: omni.log.warn( "DeprecationWarning: RigidObjectCollection.write_object_pose_to_sim will be removed in a future" " release. Please use write_object_link_pose_to_sim or write_object_com_pose_to_sim instead." ) self._root_pose_dep_warn = True self.write_object_link_pose_to_sim(object_pose, env_ids, object_ids)
[docs] def write_object_com_pose_to_sim( self, object_pose: torch.Tensor, env_ids: torch.Tensor | None = None, object_ids: slice | torch.Tensor | None = None, ): """Set the object center of mass pose over selected environment indices into the simulation. The object pose comprises of the cartesian position and quaternion orientation in (w, x, y, z). The orientation is the orientation of the principle axes of inertia. Args: object_pose: Object poses in simulation frame. Shape is (len(env_ids), len(object_ids), 7). env_ids: Environment indices. If None, then all indices are used. object_ids: Object indices. If None, then all indices are used. """ # resolve all indices if env_ids is None: local_env_ids = slice(env_ids) else: local_env_ids = env_ids if object_ids is None: local_object_ids = slice(object_ids) else: local_object_ids = object_ids com_pos = self.data.com_pos_b[local_env_ids, local_object_ids, :] com_quat = self.data.com_quat_b[local_env_ids, local_object_ids, :] object_link_pos, object_link_quat = math_utils.combine_frame_transforms( object_pose[..., :3], object_pose[..., 3:7], math_utils.quat_rotate(math_utils.quat_inv(com_quat), -com_pos), math_utils.quat_inv(com_quat), ) object_link_pose = torch.cat((object_link_pos, object_link_quat), dim=-1) self.write_object_link_pose_to_sim(object_pose=object_link_pose, env_ids=env_ids, object_ids=object_ids)
[docs] def write_object_velocity_to_sim( self, object_velocity: torch.Tensor, env_ids: torch.Tensor | None = None, object_ids: slice | torch.Tensor | None = None, ): """Set the object velocity over selected environment and object indices into the simulation. Args: object_velocity: Object velocities in simulation frame. Shape is (len(env_ids), len(object_ids), 6). env_ids: Environment indices. If None, then all indices are used. object_ids: Object indices. If None, then all indices are used. """ # deprecation warning if not self._root_vel_dep_warn: omni.log.warn( "DeprecationWarning: RigidObjectCollection.write_object_velocity_to_sim will be removed in a future" " release. Please use write_object_link_velocity_to_sim or write_object_com_velocity_to_sim instead." ) self._root_vel_dep_warn = True self.write_object_com_velocity_to_sim(object_velocity=object_velocity, env_ids=env_ids, object_ids=object_ids)
[docs] def write_object_com_velocity_to_sim( self, object_velocity: torch.Tensor, env_ids: torch.Tensor | None = None, object_ids: slice | torch.Tensor | None = None, ): """Set the object center of mass velocity over selected environment and object indices into the simulation. Args: object_velocity: Object velocities in simulation frame. Shape is (len(env_ids), len(object_ids), 6). env_ids: Environment indices. If None, then all indices are used. object_ids: Object indices. If None, then all indices are used. """ # resolve all indices # -- env_ids if env_ids is None: env_ids = self._ALL_ENV_INDICES # -- object_ids if object_ids is None: object_ids = self._ALL_OBJ_INDICES self._data.object_com_state_w[env_ids[:, None], object_ids, 7:] = object_velocity.clone() self._data._ignore_dep_warn = True self._data.object_state_w[env_ids[:, None], object_ids, 7:] = object_velocity.clone() self._data._ignore_dep_warn = False self._data.object_acc_w[env_ids[:, None], object_ids] = 0.0 # set into simulation view_ids = self._env_obj_ids_to_view_ids(env_ids, object_ids) self.root_physx_view.set_velocities( self.reshape_data_to_view(self._data.object_com_state_w[..., 7:]), indices=view_ids )
""" Operations - Setters. """
[docs] def set_external_force_and_torque( self, forces: torch.Tensor, torques: torch.Tensor, object_ids: slice | torch.Tensor | None = None, env_ids: torch.Tensor | None = None, ): """Set external force and torque to apply on the objects' bodies in their local frame. For many applications, we want to keep the applied external force on rigid bodies constant over a period of time (for instance, during the policy control). This function allows us to store the external force and torque into buffers which are then applied to the simulation at every step. .. caution:: If the function is called with empty forces and torques, then this function disables the application of external wrench to the simulation. .. code-block:: python # example of disabling external wrench asset.set_external_force_and_torque(forces=torch.zeros(0, 0, 3), torques=torch.zeros(0, 0, 3)) .. note:: This function does not apply the external wrench to the simulation. It only fills the buffers with the desired values. To apply the external wrench, call the :meth:`write_data_to_sim` function right before the simulation step. Args: forces: External forces in bodies' local frame. Shape is (len(env_ids), len(object_ids), 3). torques: External torques in bodies' local frame. Shape is (len(env_ids), len(object_ids), 3). object_ids: Object indices to apply external wrench to. Defaults to None (all objects). env_ids: Environment indices to apply external wrench to. Defaults to None (all instances). """ if forces.any() or torques.any(): self.has_external_wrench = True # resolve all indices # -- env_ids if env_ids is None: env_ids = self._ALL_ENV_INDICES # -- object_ids if object_ids is None: object_ids = self._ALL_OBJ_INDICES # set into internal buffers self._external_force_b[env_ids[:, None], object_ids] = forces self._external_torque_b[env_ids[:, None], object_ids] = torques else: self.has_external_wrench = False
""" Internal helper. """ def _initialize_impl(self): # create simulation view self._physics_sim_view = physx.create_simulation_view(self._backend) self._physics_sim_view.set_subspace_roots("/") root_prim_path_exprs = [] for name, rigid_object_cfg in self.cfg.rigid_objects.items(): # obtain the first prim in the regex expression (all others are assumed to be a copy of this) template_prim = sim_utils.find_first_matching_prim(rigid_object_cfg.prim_path) if template_prim is None: raise RuntimeError(f"Failed to find prim for expression: '{rigid_object_cfg.prim_path}'.") template_prim_path = template_prim.GetPath().pathString # find rigid root prims root_prims = sim_utils.get_all_matching_child_prims( template_prim_path, predicate=lambda prim: prim.HasAPI(UsdPhysics.RigidBodyAPI) ) if len(root_prims) == 0: raise RuntimeError( f"Failed to find a rigid body when resolving '{rigid_object_cfg.prim_path}'." " Please ensure that the prim has 'USD RigidBodyAPI' applied." ) if len(root_prims) > 1: raise RuntimeError( f"Failed to find a single rigid body when resolving '{rigid_object_cfg.prim_path}'." f" Found multiple '{root_prims}' under '{template_prim_path}'." " Please ensure that there is only one rigid body in the prim path tree." ) # check that no rigid object has an articulation root API, which decreases simulation performance articulation_prims = sim_utils.get_all_matching_child_prims( template_prim_path, predicate=lambda prim: prim.HasAPI(UsdPhysics.ArticulationRootAPI) ) if len(articulation_prims) != 0: if articulation_prims[0].GetAttribute("physxArticulation:articulationEnabled").Get(): raise RuntimeError( f"Found an articulation root when resolving '{rigid_object_cfg.prim_path}' in the rigid object" f" collection. These are located at: '{articulation_prims}' under '{template_prim_path}'." " Please disable the articulation root in the USD or from code by setting the parameter" " 'ArticulationRootPropertiesCfg.articulation_enabled' to False in the spawn configuration." ) # resolve root prim back into regex expression root_prim_path = root_prims[0].GetPath().pathString root_prim_path_expr = rigid_object_cfg.prim_path + root_prim_path[len(template_prim_path) :] root_prim_path_exprs.append(root_prim_path_expr.replace(".*", "*")) self._object_names_list.append(name) # -- object view self._root_physx_view = self._physics_sim_view.create_rigid_body_view(root_prim_path_exprs) # check if the rigid body was created if self._root_physx_view._backend is None: raise RuntimeError("Failed to create rigid body collection. Please check PhysX logs.") # log information about the rigid body omni.log.info(f"Number of instances: {self.num_instances}") omni.log.info(f"Number of distinct objects: {self.num_objects}") omni.log.info(f"Object names: {self.object_names}") # container for data access self._data = RigidObjectCollectionData(self.root_physx_view, self.num_objects, self.device) # create buffers self._create_buffers() # process configuration self._process_cfg() # update the rigid body data self.update(0.0) def _create_buffers(self): """Create buffers for storing data.""" # constants self._ALL_ENV_INDICES = torch.arange(self.num_instances, dtype=torch.long, device=self.device) self._ALL_OBJ_INDICES = torch.arange(self.num_objects, dtype=torch.long, device=self.device) # external forces and torques self.has_external_wrench = False self._external_force_b = torch.zeros((self.num_instances, self.num_objects, 3), device=self.device) self._external_torque_b = torch.zeros_like(self._external_force_b) # set information about rigid body into data self._data.object_names = self.object_names self._data.default_mass = self.reshape_view_to_data(self.root_physx_view.get_masses().clone()) self._data.default_inertia = self.reshape_view_to_data(self.root_physx_view.get_inertias().clone()) def _process_cfg(self): """Post processing of configuration parameters.""" # default state # -- object state default_object_states = [] for rigid_object_cfg in self.cfg.rigid_objects.values(): default_object_state = ( tuple(rigid_object_cfg.init_state.pos) + tuple(rigid_object_cfg.init_state.rot) + tuple(rigid_object_cfg.init_state.lin_vel) + tuple(rigid_object_cfg.init_state.ang_vel) ) default_object_state = ( torch.tensor(default_object_state, dtype=torch.float, device=self.device) .repeat(self.num_instances, 1) .unsqueeze(1) ) default_object_states.append(default_object_state) # concatenate the default state for each object default_object_states = torch.cat(default_object_states, dim=1) self._data.default_object_state = default_object_states
[docs] def reshape_view_to_data(self, data: torch.Tensor) -> torch.Tensor: """Reshapes and arranges the data coming from the :attr:`root_physx_view` to (num_instances, num_objects, data_size). Args: data: The data coming from the :attr:`root_physx_view`. Shape is (num_instances*num_objects, data_size). Returns: The reshaped data. Shape is (num_instances, num_objects, data_size). """ return torch.einsum("ijk -> jik", data.reshape(self.num_objects, self.num_instances, -1))
[docs] def reshape_data_to_view(self, data: torch.Tensor) -> torch.Tensor: """Reshapes and arranges the data to the be consistent with data from the :attr:`root_physx_view`. Args: data: The data to be reshaped. Shape is (num_instances, num_objects, data_size). Returns: The reshaped data. Shape is (num_instances*num_objects, data_size). """ return torch.einsum("ijk -> jik", data).reshape(self.num_objects * self.num_instances, *data.shape[2:])
def _env_obj_ids_to_view_ids( self, env_ids: torch.Tensor, object_ids: Sequence[int] | slice | torch.Tensor ) -> torch.Tensor: """Converts environment and object indices to indices consistent with data from :attr:`root_physx_view`. Args: env_ids: Environment indices. object_ids: Object indices. Returns: The view indices. """ # the order is env_0/object_0, env_0/object_1, env_0/object_..., env_1/object_0, env_1/object_1, ... # return a flat tensor of indices if isinstance(object_ids, slice): object_ids = self._ALL_OBJ_INDICES elif isinstance(object_ids, Sequence): object_ids = torch.tensor(object_ids, device=self.device) return (object_ids.unsqueeze(1) * self.num_instances + env_ids).flatten() """ Internal simulation callbacks. """ def _invalidate_initialize_callback(self, event): """Invalidates the scene elements.""" # call parent super()._invalidate_initialize_callback(event) # set all existing views to None to invalidate them self._physics_sim_view = None self._root_physx_view = None