Merge the rebuilt handover and camera manager base

# Conflicts:
#	source/isaaclab_tasks/changelog.d/task-cleanup-dex-part08.major.rst
#	source/isaaclab_tasks/isaaclab_tasks/core/reorient/mdp/__init__.pyi
#	source/isaaclab_tasks/isaaclab_tasks/core/reorient/mdp/rewards.py
#	source/isaaclab_tasks/isaaclab_tasks/core/reorient/mdp/terminations.py
#	source/isaaclab_tasks/isaaclab_tasks/core/reorient/reorient_manager_env_cfg.py

Author: hujc7

source/isaaclab_tasks/changelog.d/task-cleanup-dex-part08.major.rst

@@ -10,17 +10,14 @@ Added
   retraining).
 * Added a Newton physics preset to the manager-based Allegro environment.
 
-Deprecated
-^^^^^^^^^^
+Removed
+^^^^^^^
 
-* Deprecated the legacy manager-based reorientation configuration
-  :class:`~isaaclab_tasks.core.reorient.reorient_manager_env_cfg.ReorientObjectEnvCfg`
-  and the manager terms only it consumes (:func:`~isaaclab_tasks.core.reorient.mdp.success_bonus`,
-  :func:`~isaaclab_tasks.core.reorient.mdp.track_pos_l2`,
-  :func:`~isaaclab_tasks.core.reorient.mdp.track_orientation_inv_l2`,
-  :func:`~isaaclab_tasks.core.reorient.mdp.max_consecutive_success`, and
-  :func:`~isaaclab_tasks.core.reorient.mdp.object_away_from_goal`) in favor of
-  the Direct-compatible manager configurations and terms (e.g.
+* Removed the legacy manager-based reorientation configuration
+  ``ReorientObjectEnvCfg`` and the manager terms only it consumed
+  (``success_bonus``, ``track_pos_l2``, ``track_orientation_inv_l2``,
+  ``max_consecutive_success``, and ``object_away_from_goal``). Use the
+  Direct-compatible manager configurations and terms instead (e.g.
   :class:`~isaaclab_tasks.core.reorient.mdp.ReorientReward` and
   :class:`~isaaclab_tasks.core.reorient.mdp.ReorientTimeout`).
 

source/isaaclab_tasks/isaaclab_tasks/core/reorient/__init__.py

@@ -8,10 +8,9 @@
 This package consolidates the direct-workflow and manager-based-workflow in-hand
 manipulation tasks, where a dexterous hand reorients an object to match a goal
 orientation. The shared direct base environment lives in
-:mod:`~isaaclab_tasks.core.reorient.reorient_direct_env` and the shared manager-based
-base configuration in :mod:`~isaaclab_tasks.core.reorient.reorient_manager_env_cfg`.
-Robot-specific tasks are organized under the ``config`` subpackage
-(``config/allegro_hand`` and ``config/shadow_hand``).
+:mod:`~isaaclab_tasks.core.reorient.reorient_direct_env`; the manager-based
+configurations live with their robot-specific tasks under the ``config``
+subpackage (``config/allegro_hand`` and ``config/shadow_hand``).
 
 These environments are based on the `dexterous cube manipulation`_ environments
 provided in IsaacGymEnvs repository from NVIDIA. However, they contain certain

source/isaaclab_tasks/isaaclab_tasks/core/reorient/mdp/__init__.pyi

@@ -21,14 +21,9 @@ __all__ = [
     "reorient_last_action",
     "OpenAIPolicyObservation",
     "goal_quat_diff",
-    "success_bonus",
-    "track_orientation_inv_l2",
-    "track_pos_l2",
     "evaluate_reorient_success",
     "reorient_reward",
     "ReorientReward",
-    "max_consecutive_success",
-    "object_away_from_goal",
     "object_away_from_robot",
     "object_reorientation_out_of_reach",
     "ReorientTimeout",
@@ -56,14 +51,9 @@ from .rewards import (
     ReorientReward,
     reorient_reward,
     evaluate_reorient_success,
-    success_bonus,
-    track_orientation_inv_l2,
-    track_pos_l2,
 )
 from .terminations import (
     ReorientTimeout,
-    max_consecutive_success,
-    object_away_from_goal,
     object_away_from_robot,
     object_reorientation_out_of_reach,
 )

source/isaaclab_tasks/isaaclab_tasks/core/reorient/mdp/rewards.py

@@ -7,7 +7,6 @@
 
 from __future__ import annotations
 
-import warnings
 from collections.abc import Sequence
 from typing import TYPE_CHECKING
 
@@ -22,123 +21,6 @@
     from isaaclab.assets import RigidObject
     from isaaclab.envs import ManagerBasedRLEnv
 
-    from .commands import ReorientCommand
-
-
-def success_bonus(
-    env: ManagerBasedRLEnv, command_name: str, object_cfg: SceneEntityCfg = SceneEntityCfg("object")
-) -> torch.Tensor:
-    """Bonus reward for successfully reaching the goal.
-
-    .. deprecated:: 9.0.0
-        Only consumed by the deprecated
-        :class:`~isaaclab_tasks.core.reorient.reorient_manager_env_cfg.ReorientObjectEnvCfg`.
-        Use :class:`ReorientReward` instead.
-
-    The object is considered to have reached the goal when the object orientation is within the threshold.
-    The reward is 1.0 if the object has reached the goal, otherwise 0.0.
-
-    Args:
-        env: The environment object.
-        command_name: The command term to be used for extracting the goal.
-        object_cfg: The configuration for the scene entity. Default is "object".
-    """
-    if not getattr(success_bonus, "_deprecation_warned", False):
-        success_bonus._deprecation_warned = True
-        warnings.warn(
-            "success_bonus() is deprecated; use ReorientReward instead.",
-            DeprecationWarning,
-            stacklevel=2,
-        )
-    # extract useful elements
-    asset: RigidObject = env.scene[object_cfg.name]
-    command_term: ReorientCommand = env.command_manager.get_term(command_name)
-
-    # obtain the goal orientation
-    goal_quat_w = command_term.command[:, 3:7]
-    # obtain the threshold for the orientation error
-    threshold = command_term.cfg.orientation_success_threshold
-    # calculate the orientation error
-    dtheta = math_utils.quat_error_magnitude(asset.data.root_quat_w.torch, goal_quat_w)
-
-    return dtheta <= threshold
-
-
-def track_pos_l2(
-    env: ManagerBasedRLEnv, command_name: str, object_cfg: SceneEntityCfg = SceneEntityCfg("object")
-) -> torch.Tensor:
-    """Reward for tracking the object position using the L2 norm.
-
-    .. deprecated:: 9.0.0
-        Only consumed by the deprecated
-        :class:`~isaaclab_tasks.core.reorient.reorient_manager_env_cfg.ReorientObjectEnvCfg`.
-        Use :class:`ReorientReward` instead.
-
-    The reward is the distance between the object position and the goal position.
-
-    Args:
-        env: The environment object.
-        command_term: The command term to be used for extracting the goal.
-        object_cfg: The configuration for the scene entity. Default is "object".
-    """
-    if not getattr(track_pos_l2, "_deprecation_warned", False):
-        track_pos_l2._deprecation_warned = True
-        warnings.warn(
-            "track_pos_l2() is deprecated; use ReorientReward instead.",
-            DeprecationWarning,
-            stacklevel=2,
-        )
-    # extract useful elements
-    asset: RigidObject = env.scene[object_cfg.name]
-    command_term: ReorientCommand = env.command_manager.get_term(command_name)
-
-    # obtain the goal position
-    goal_pos_e = command_term.command[:, 0:3]
-    # obtain the object position in the environment frame
-    object_pos_e = asset.data.root_pos_w.torch - env.scene.env_origins
-
-    return torch.linalg.norm(goal_pos_e - object_pos_e, ord=2, dim=-1)
-
-
-def track_orientation_inv_l2(
-    env: ManagerBasedRLEnv,
-    command_name: str,
-    object_cfg: SceneEntityCfg = SceneEntityCfg("object"),
-    rot_eps: float = 1e-3,
-) -> torch.Tensor:
-    """Reward for tracking the object orientation using the inverse of the orientation error.
-
-    .. deprecated:: 9.0.0
-        Only consumed by the deprecated
-        :class:`~isaaclab_tasks.core.reorient.reorient_manager_env_cfg.ReorientObjectEnvCfg`.
-        Use :class:`ReorientReward` instead.
-
-    The reward is the inverse of the orientation error between the object orientation and the goal orientation.
-
-    Args:
-        env: The environment object.
-        command_name: The command term to be used for extracting the goal.
-        object_cfg: The configuration for the scene entity. Default is "object".
-        rot_eps: The threshold for the orientation error. Default is 1e-3.
-    """
-    if not getattr(track_orientation_inv_l2, "_deprecation_warned", False):
-        track_orientation_inv_l2._deprecation_warned = True
-        warnings.warn(
-            "track_orientation_inv_l2() is deprecated; use ReorientReward instead.",
-            DeprecationWarning,
-            stacklevel=2,
-        )
-    # extract useful elements
-    asset: RigidObject = env.scene[object_cfg.name]
-    command_term: ReorientCommand = env.command_manager.get_term(command_name)
-
-    # obtain the goal orientation
-    goal_quat_w = command_term.command[:, 3:7]
-    # calculate the orientation error
-    dtheta = math_utils.quat_error_magnitude(asset.data.root_quat_w.torch, goal_quat_w)
-
-    return 1.0 / (dtheta + rot_eps)
-
 
 @torch.jit.script
 def evaluate_reorient_success(

source/isaaclab_tasks/isaaclab_tasks/core/reorient/mdp/terminations.py

@@ -7,7 +7,6 @@
 
 from __future__ import annotations
 
-import warnings
 from typing import TYPE_CHECKING
 
 import torch
@@ -22,71 +21,6 @@
     from .commands import ReorientCommand
 
 
-def max_consecutive_success(env: ManagerBasedRLEnv, num_success: int, command_name: str) -> torch.Tensor:
-    """Check if the task has been completed consecutively for a certain number of times.
-
-    .. deprecated:: 9.0.0
-        Only consumed by the deprecated
-        :class:`~isaaclab_tasks.core.reorient.reorient_manager_env_cfg.ReorientObjectEnvCfg`.
-        Use :class:`ReorientTimeout` instead.
-
-    Args:
-        env: The environment object.
-        num_success: Threshold for the number of consecutive successes required.
-        command_name: The command term to be used for extracting the goal.
-    """
-    if not globals().get("_warned_max_consecutive_success"):
-        globals()["_warned_max_consecutive_success"] = True
-        warnings.warn(
-            "max_consecutive_success() is deprecated; use ReorientTimeout instead.",
-            DeprecationWarning,
-            stacklevel=2,
-        )
-    command_term: ReorientCommand = env.command_manager.get_term(command_name)
-
-    return command_term.metrics["consecutive_success"] >= num_success
-
-
-def object_away_from_goal(
-    env: ManagerBasedRLEnv,
-    threshold: float,
-    command_name: str,
-    object_cfg: SceneEntityCfg = SceneEntityCfg("object"),
-) -> torch.Tensor:
-    """Check if object has gone far from the goal.
-
-    The object is considered to be out-of-reach if the distance between the goal and the object is greater
-    than the threshold.
-
-    .. deprecated:: 9.0.0
-        Only consumed by the deprecated
-        :class:`~isaaclab_tasks.core.reorient.reorient_manager_env_cfg.ReorientObjectEnvCfg`.
-        Use :class:`object_reorientation_out_of_reach` instead.
-
-    Args:
-        env: The environment object.
-        threshold: The threshold for the distance between the robot and the object.
-        command_name: The command term to be used for extracting the goal.
-        object_cfg: The configuration for the scene entity. Default is "object".
-    """
-    if not globals().get("_warned_object_away_from_goal"):
-        globals()["_warned_object_away_from_goal"] = True
-        warnings.warn(
-            "object_away_from_goal() is deprecated; use object_reorientation_out_of_reach instead.",
-            DeprecationWarning,
-            stacklevel=2,
-        )
-    # extract useful elements
-    command_term: ReorientCommand = env.command_manager.get_term(command_name)
-    asset = env.scene[object_cfg.name]
-
-    # object pos
-    asset_pos_e = asset.data.root_pos_w.torch - env.scene.env_origins
-    goal_pos_e = command_term.command[:, :3]
-
-    return torch.linalg.norm(asset_pos_e - goal_pos_e, ord=2, dim=1) > threshold
-
-
 class object_reorientation_out_of_reach(ManagerTermBase):
     """Terminate when object-to-goal distance is at least the threshold [m].