# Copyright (c) 2024-2025, The Isaac Lab Project Developers.
# All rights reserved.
#
# SPDX-License-Identifier: Apache-2.0
from isaaclab.envs.mimic_env_cfg import MimicEnvCfg, SubTaskConfig
from isaaclab.utils import configclass
from isaaclab_tasks.manager_based.manipulation.stack.config.franka.stack_ik_rel_env_cfg import FrankaCubeStackEnvCfg
[docs]@configclass
class FrankaCubeStackIKRelMimicEnvCfg(FrankaCubeStackEnvCfg, MimicEnvCfg):
"""
Isaac Lab Mimic environment config class for Franka Cube Stack IK Rel env.
"""
def __post_init__(self):
# post init of parents
super().__post_init__()
# # TODO: Figure out how we can move this to the MimicEnvCfg class
# # The __post_init__() above only calls the init for FrankaCubeStackEnvCfg and not MimicEnvCfg
# # https://stackoverflow.com/questions/59986413/achieving-multiple-inheritance-using-python-dataclasses
# Override the existing values
self.datagen_config.name = "demo_src_stack_isaac_lab_task_D0"
self.datagen_config.generation_guarantee = True
self.datagen_config.generation_keep_failed = True
self.datagen_config.generation_num_trials = 10
self.datagen_config.generation_select_src_per_subtask = True
self.datagen_config.generation_transform_first_robot_pose = False
self.datagen_config.generation_interpolate_from_last_target_pose = True
self.datagen_config.max_num_failures = 25
self.datagen_config.seed = 1
# The following are the subtask configurations for the stack task.
subtask_configs = []
subtask_configs.append(
SubTaskConfig(
# Each subtask involves manipulation with respect to a single object frame.
object_ref="cube_2",
# This key corresponds to the binary indicator in "datagen_info" that signals
# when this subtask is finished (e.g., on a 0 to 1 edge).
subtask_term_signal="grasp_1",
# Specifies time offsets for data generation when splitting a trajectory into
# subtask segments. Random offsets are added to the termination boundary.
subtask_term_offset_range=(10, 20),
# Selection strategy for the source subtask segment during data generation
selection_strategy="nearest_neighbor_object",
# Optional parameters for the selection strategy function
selection_strategy_kwargs={"nn_k": 3},
# Amount of action noise to apply during this subtask
action_noise=0.03,
# Number of interpolation steps to bridge to this subtask segment
num_interpolation_steps=5,
# Additional fixed steps for the robot to reach the necessary pose
num_fixed_steps=0,
# If True, apply action noise during the interpolation phase and execution
apply_noise_during_interpolation=False,
)
)
subtask_configs.append(
SubTaskConfig(
# Each subtask involves manipulation with respect to a single object frame.
object_ref="cube_1",
# Corresponding key for the binary indicator in "datagen_info" for completion
subtask_term_signal="stack_1",
# Time offsets for data generation when splitting a trajectory
subtask_term_offset_range=(10, 20),
# Selection strategy for source subtask segment
selection_strategy="nearest_neighbor_object",
# Optional parameters for the selection strategy function
selection_strategy_kwargs={"nn_k": 3},
# Amount of action noise to apply during this subtask
action_noise=0.03,
# Number of interpolation steps to bridge to this subtask segment
num_interpolation_steps=5,
# Additional fixed steps for the robot to reach the necessary pose
num_fixed_steps=0,
# If True, apply action noise during the interpolation phase and execution
apply_noise_during_interpolation=False,
)
)
subtask_configs.append(
SubTaskConfig(
# Each subtask involves manipulation with respect to a single object frame.
object_ref="cube_3",
# Corresponding key for the binary indicator in "datagen_info" for completion
subtask_term_signal="grasp_2",
# Time offsets for data generation when splitting a trajectory
subtask_term_offset_range=(10, 20),
# Selection strategy for source subtask segment
selection_strategy="nearest_neighbor_object",
# Optional parameters for the selection strategy function
selection_strategy_kwargs={"nn_k": 3},
# Amount of action noise to apply during this subtask
action_noise=0.03,
# Number of interpolation steps to bridge to this subtask segment
num_interpolation_steps=5,
# Additional fixed steps for the robot to reach the necessary pose
num_fixed_steps=0,
# If True, apply action noise during the interpolation phase and execution
apply_noise_during_interpolation=False,
)
)
subtask_configs.append(
SubTaskConfig(
# Each subtask involves manipulation with respect to a single object frame.
object_ref="cube_2",
# End of final subtask does not need to be detected
subtask_term_signal=None,
# No time offsets for the final subtask
subtask_term_offset_range=(0, 0),
# Selection strategy for source subtask segment
selection_strategy="nearest_neighbor_object",
# Optional parameters for the selection strategy function
selection_strategy_kwargs={"nn_k": 3},
# Amount of action noise to apply during this subtask
action_noise=0.03,
# Number of interpolation steps to bridge to this subtask segment
num_interpolation_steps=5,
# Additional fixed steps for the robot to reach the necessary pose
num_fixed_steps=0,
# If True, apply action noise during the interpolation phase and execution
apply_noise_during_interpolation=False,
)
)
self.subtask_configs["franka"] = subtask_configs
