Use the unified collision checking for consistency with sampling functions.

Use the unified collision checking for consistency with sampling functions.

Use the unified collision checking for consistency with sampling functions.

Use the unified collision checking for consistency with sampling functions.

Use the unified collision checking for consistency with sampling functions.

Use the unified collision checking for consistency with sampling functions.

Use the unified collision checking for consistency with sampling functions.

Use the unified collision checking for consistency with sampling functions.

Use the unified collision checking for consistency with sampling functions.

Compute objective function values

Compute the position and orientation error between source and target frames. Args: t01: Position of source frame. Shape is (N, 3).

Create a warp mesh object with a mesh defined from vertices and triangles. Args: points: The vertices of the mesh. Shape is (N, 3), where

Create a door mesh positioned on the wall.

robot_qpos: (1, num_joints) current_ee_pos: (1, 3) target_ee_pos: (1, 3) target_ee_quat: (1, 4) return: traj: (num_steps

Fast distance calculation with approximations.

Applies rotation from Euler XYZ on position vector.

Find shared wall segments between two rooms. Args: room1: First room data room2: Second room data Returns:

Updates articulation kinematics and fabric for rendering.

Get path to the model checkpoint in input directory. The checkpoint file is resolved as: ``<log_path>/<run_dir>/<*other_dirs>/<checkpoint>``, whe

Get current environment simulator state as a dictionary. Should be compatible with @reset_to.

Get the state of the specified index from the dataset.

Retrieves the time logged in the global dictionary based on name. Args: name: Name of the the entry to be retrieved.

Loads an input PKL file safely. Args: filename: The path to pickled file. Raises: FileNotFoundError: When the specified file

Generate a plane mesh. If :obj:`center_zero` is True, the origin is at center of the plane mesh i.e. the mesh extends from :math:`(-size[0] /

Apply function @func to torch.Tensor objects in a nested dictionary or list or tuple. Args: x (dict or list or tuple): a possibl

Utility function for the common use case where either an ckpt path or a ckpt_dict is provided. This is a no-op if ckpt_dict is not None,

Prepares an observation @obs of this modality for network input. Args: obs (np.array or torch.Tensor): raw observation,

Convert rotations given as angle-axis to quaternions. Args: angle: The angle turned anti-clockwise in radians around the vector's directi

Converts Euler XYZ to Quaternion (w, x, y, z).

Calculate the angle between two quaternions. Parameters: q1, q2: Lists or arrays of shape [w, x, y, z] representing quaternions Ret

Returns sampled rotation in 3D as quaternion. Args: num: The number of rotations to sample. device: Device to create tensor on.

Resets the scene entities. Args: env_ids: The indices of the environments to reset. Defaults to None (all instanc

Get dictionary of current model parameters.

Set joint velocity targets into internal buffers. .. note:: This function does not apply the joint targets to the simulation. It

Sets the time lag for the delay buffer across the provided batch indices. Args: time_lag: The desired delay for the buffer.

Start timing.

Execute one time-step of the environment's dynamics. The environment steps forward at a fixed time-step, while the physics simulation is

Update the scene entities. Args: dt: The amount of time passed from last :meth:`update` call.

Validate room layout for overlaps, connectivity issues, and door/window placement. Args: rooms_data: List of room dictionaries f

Args: input_obs_group_shapes (OrderedDict): a dictionary of dictionaries. Each key in this dictionary should spec

Helper function to escape HTML characters

Resolve common term configuration. Usually, called by the :meth:`_prepare_terms` method to resolve common term configuration. Note:

Create a USDGeom-based prim with the given attributes. To make the asset instanceable, we must follow a certain structure dictated by how USD sce

Create a `USDGeomMesh`_ prim from the given mesh. This function is similar to :func:`shapes._spawn_geom_from_prim_type` but spawns the prim from

Validate the properties on the prim. Args: prim_path: The prim name. cfg: The configuration for the light source.

Factory function for creating algorithms based on the algorithm name and config. Args: algo_name (str): the algorithm name

Apply position and rotation transforms to an object mesh. Args: mesh: The original mesh (untransformed) obj: Object cont

Remove C-style comments (// and /* */ comment text) from a JSON string while preserving any comment markers that appear inside string values

Close the dataset file handler.

Cleanup for the environment.

r"""Converts a quaternion representing a rotation from one convention to another. In USD, the camera follows the ``"opengl"`` convention. Thus, i

Creates a new hdf5 filter key in hdf5 file @hdf5_path with name @key_name that corresponds to the demonstrations @demo_keys. Filter keys

Create a unified occupancy grid that will be consistent across all functions. Returns: tuple: (occupancy_grid, grid_x, grid_y, r

Create a unified occupancy grid that will be consistent across all functions. Returns: tuple: (occupancy_grid, grid_x, grid_y, r

Create a unified occupancy grid that will be consistent across all functions. Returns: tuple: (occupancy_grid, grid_x, grid_y, r

Create a unified occupancy grid that will be consistent across all functions. Returns: tuple: (occupancy_grid, grid_x, grid_y, r

Create a unified occupancy grid that will be consistent across all functions. Returns: tuple: (occupancy_grid, grid_x, grid_y, r

Create a unified occupancy grid that will be consistent across all functions. Returns: tuple: (occupancy_grid, grid_x, grid_y, r

Create a unified occupancy grid that will be consistent across all functions. Returns: tuple: (occupancy_grid, grid_x, grid_y, r

Create a unified occupancy grid that will be consistent across all functions. Returns: tuple: (occupancy_grid, grid_x, grid_y, r

Create a unified occupancy grid that will be consistent across all functions. Returns: tuple: (occupancy_grid, grid_x, grid_y, r