habitat.tasks.rearrange.utils module

Classes

class CacheHelper

class CollisionDetails

class IkHelper

class UsesArticulatedAgentInterface

For sensors or actions that are agent specific. Used to split actions and sensors between multiple agents.

Functions

def _get_robot_spawns(target_position: numpy.ndarray, rotation_perturbation_noise: float, distance_threshold: float, sim, num_spawn_attempts: int, filter_colliding_states: bool, agent: typing.Optional[articulated_agents.MobileManipulator] = None) -> typing.Tuple[_magnum.Vector3, float, bool]

Attempts to place the robot near the target position, facing towards it. This does NOT set the position or angle of the robot, even if a place is successful.

def _place_robot_at_closest_point(target_position: numpy.ndarray, sim, agent: typing.Optional[articulated_agents.MobileManipulator] = None)

Gets the agent’s position and orientation at the closest point to the target position. :return: The robot’s start position, rotation, and whether the placement was a failure (True for failure, False for success).

def add_perf_timing_func(name: typing.Optional[str] = None)

Function decorator for logging the speed of a method to the RearrangeSim. This must either be applied to methods from RearrangeSim or to methods from objects that contain self._sim so this decorator can access the underlying RearrangeSim instance to log the speed. This scopes the logging name so nested function calls will include the outer perf timing name separate by a “.”.

def allowed_region_to_bb(allowed_region)

def angle_between(v1: typing.Tuple[_magnum.Vector3, numpy.ndarray, typing.List], v2: typing.Tuple[_magnum.Vector3, numpy.ndarray, typing.List]) -> float

Angle (in radians) between two vectors

def batch_transform_point(points: numpy.ndarray, transform_matrix: _magnum.Matrix4, dtype = <class 'numpy.float32'>) -> numpy.ndarray

def coll_link_name_matches(coll, name)

def coll_name_matches(coll, name)

def convert_legacy_cfg(obj_list)

def euler_to_quat(rpy)

def get_aabb(obj_id, sim, transformed = False)

def get_angle_to_pos(rel_pos: numpy.ndarray) -> float

def get_ao_link_aabb(ao_obj_id: int, link_id: int, sim: habitat_sim.simulator.Simulator, transformed: bool = False) -> typing.Optional[_magnum.Range3D]

Get the AABB for a link of an ArticulatedObject. Returns None if object or link are not found.

def get_camera_lookat_relative_to_vertial_line(agent) -> float

Get the camera looking angles to a vertical line to the ground

def get_camera_object_angle(cam_T: _magnum.Matrix4, obj_pos: typing.Tuple[_magnum.Vector3, numpy.ndarray, typing.List], center_cone_vector: typing.Tuple[_magnum.Vector3, numpy.ndarray, typing.List]) -> float

Calculates angle between camera line-of-sight and given global position

def get_camera_transform(cur_articulated_agent) -> _magnum.Matrix4

Get the camera transformation

def get_match_link(coll, name)

def get_rigid_aabb(obj_id: int, sim: habitat_sim.simulator.Simulator, transformed: bool = False) -> typing.Optional[_magnum.Range3D]

Get the AABB for a RigidObject. Returns None if object is not found.

def is_pb_installed()

def make_border_red(img)

def make_render_only(obj, sim)

def place_agent_at_dist_from_pos(target_position: numpy.ndarray, rotation_perturbation_noise: float, distance_threshold: float, sim, num_spawn_attempts: int, filter_colliding_states: bool, agent: typing.Optional[articulated_agents.MobileManipulator] = None, navmesh_offset: typing.Optional[typing.List[typing.Tuple[float, float]]] = None)

Places the robot at closest point if distance_threshold is -1.0 otherwise will place the robot at distance_threshold away.

def place_robot_at_closest_point_with_navmesh(target_position: numpy.ndarray, sim, navmesh_offset: typing.Optional[typing.List[typing.Tuple[float, float]]] = None, agent: typing.Optional[articulated_agents.MobileManipulator] = None)

Gets the agent’s position and orientation at the closest point to the target position. :return: The robot’s start position, rotation, and whether the placement was a failure (True for failure, False for success).

def rearrange_collision(sim, count_obj_colls: bool, verbose: bool = False, ignore_names: typing.Optional[typing.List[str]] = None, ignore_base: bool = True, get_extra_coll_data: bool = False, agent_idx: typing.Optional[int] = None)

Defines what counts as a collision for the Rearrange environment execution

def set_agent_base_via_obj_trans(position: numpy.ndarray, rotation: float, agent)

Set the agent’s base position and rotation via object transformation

def write_gfx_replay(gfx_keyframe_str, task_config, ep_id)

Writes the all replay frames to a file for later replay. Filename is of the form ‘episodeX.replay.json’ where X is the episode ID.

Data

p = None

Function documentation