def __init__(self, env, action_repeat=1, gripper=False):
"""
Initializes the inverse kinematics wrapper.
This wrapper allows for controlling the robot through end effector
movements instead of joint velocities.
Args:
env (MujocoEnv instance): The environment to wrap.
action_repeat (int): Determines the number of times low-level joint
control actions will be commanded per high-level end effector
action. Higher values will allow for more precise control of
the end effector to the commanded targets.
"""
super().__init__(env)
self.action_spec = env.action_spec
if self.env.mujoco_robot.name == "sawyer":
self.controller = SawyerIKController(
bullet_data_path=os.path.join(robosuite.models.assets_root,
"bullet_data"),
robot_jpos_getter=self._robot_jpos_getter,
)
else:
raise Exception("Only Sawyer robot environments supported for IK "
"control currently.")
self.action_repeat = action_repeat
self.gripper = gripper
def __init__(self, env):
"""
Initializes the inverse kinematics wrapper.
This wrapper allows for controlling the robot through end effector
movements instead of joint velocities.
Args:
env (MujocoEnv instance): The environment to wrap.
"""
super().__init__(env)
if self.env.mujoco_robot.name == "sawyer":
from robosuite.controllers import SawyerIKController
self.controller = SawyerIKController(
bullet_data_path=os.path.join(robosuite.models.assets_root,
"bullet_data"),
robot_jpos_getter=self._robot_jpos_getter,
)
elif self.env.mujoco_robot.name == "baxter":
from robosuite.controllers import BaxterIKController
self.controller = BaxterIKController(
bullet_data_path=os.path.join(robosuite.models.assets_root,
"bullet_data"),
robot_jpos_getter=self._robot_jpos_getter,
)
else:
raise Exception(
"Only Sawyer and Baxter robot environments are supported for IK "
"control currently.")
def __init__(self, env):
self.env = env.wrapped_env.env
self.controller = SawyerIKController(
bullet_data_path=os.path.join(robosuite.models.assets_root,
"bullet_data"),
robot_jpos_getter=self._robot_jpos_getter,
)
def __init__(self, jpos, quat):
self.jpos = jpos
self.quat = quat
self.controller = SawyerIKController(
bullet_data_path=os.path.join(robosuite.models.assets_root,
"bullet_data"),
robot_jpos_getter=self._robot_jpos_getter,
)
def __init__(
self,
gripper_type="TwoFingerGripper",
lower_goal_range=[-0.1, -0.1, -0.1],
upper_goal_range=[0.1, 0.1, 0.2],
seed=False,
random_arm_init=None, # please pass in [low, high]
table_full_size=(0.8, 0.8, 0.6),
table_friction=(1., 5e-3, 1e-4),
use_camera_obs=False,
use_object_obs=True,
reward_shaping=True,
placement_initializer=None,
gripper_visualization=False,
use_indicator_object=False,
has_renderer=False,
has_offscreen_renderer=True,
render_collision_mesh=False,
render_visual_mesh=True,
control_freq=10,
horizon=1000,
ignore_done=False,
camera_name="frontview",
camera_height=256,
camera_width=256,
camera_depth=False,
):
"""
Args:
prim_axis (str): which axis is being explored
gripper_type (str): type of gripper, used to instantiate
gripper models from gripper factory.
table_full_size (3-tuple): x, y, and z dimensions of the table.
table_friction (3-tuple): the three mujoco friction parameters for
the table.
use_camera_obs (bool): if True, every observation includes a
rendered image.
use_object_obs (bool): if True, include object (cube) information in
the observation.
reward_shaping (bool): if True, use dense rewards.
placement_initializer (ObjectPositionSampler instance): if provided, will
be used to place objects on every reset, else a UniformRandomSampler
is used by default.
gripper_visualization (bool): True if using gripper visualization.
Useful for teleoperation.
use_indicator_object (bool): if True, sets up an indicator object that
is useful for debugging.
has_renderer (bool): If true, render the simulation state in
a viewer instead of headless mode.
has_offscreen_renderer (bool): True if using off-screen rendering.
render_collision_mesh (bool): True if rendering collision meshes
in camera. False otherwise.
render_visual_mesh (bool): True if rendering visual meshes
in camera. False otherwise.
control_freq (float): how many control signals to receive
in every second. This sets the amount of simulation time
that passes between every action input.
horizon (int): Every episode lasts for exactly @horizon timesteps.
ignore_done (bool): True if never terminating the environment (ignore @horizon).
camera_name (str): name of camera to be rendered. Must be
set if @use_camera_obs is True.
camera_height (int): height of camera frame.
camera_width (int): width of camera frame.
camera_depth (bool): True if rendering RGB-D, and RGB otherwise.
"""
self.upper_goal_range = upper_goal_range
self.lower_goal_range = lower_goal_range
self.random_arm_init = random_arm_init
self.seed = seed
self.distance_threshold = 0.015
# settings for table top
self.table_full_size = table_full_size
self.table_friction = table_friction
# whether to use ground-truth object states
self.use_object_obs = use_object_obs
# reward configuration
self.reward_shaping = reward_shaping
# object placement initializer
self.placement_initializer = placement_initializer
# order: di["eef_pos"] di["gripper_qpos"] di["gripper_to_marker"] self.goal
# dim: 3, 2, 3, 3
# low = -np.ones(11) * np.inf
# high = np.ones(11) * np.inf
# self.observation_space = spaces.Box(low=low, high=high)
self.controller = SawyerIKController(
bullet_data_path=os.path.join(robosuite.models.assets_root,
"bullet_data"),
robot_jpos_getter=self._robot_jpos_getter,
)
super().__init__(
gripper_type=gripper_type,
gripper_visualization=gripper_visualization,
use_indicator_object=use_indicator_object,
has_renderer=has_renderer,
has_offscreen_renderer=has_offscreen_renderer,
render_collision_mesh=render_collision_mesh,
render_visual_mesh=render_visual_mesh,
control_freq=control_freq,
horizon=horizon,
ignore_done=ignore_done,
use_camera_obs=use_camera_obs,
camera_name=camera_name,
camera_height=camera_height,
camera_width=camera_width,
camera_depth=camera_depth,
)