Robot

Initializes a robot simulation object, as defined by a single corresponding robot XML

Parameters

• robot_type (str) – Specification for specific robot arm to be instantiated within this env (e.g: “Panda”)

• idn (int or str) – Unique ID of this robot. Should be different from others

• initial_qpos (sequence of float) – If set, determines the initial joint positions of the robot to be instantiated for the task

• initialization_noise (dict) –

  Dict containing the initialization noise parameters. The expected keys and corresponding value types are specified below:

  ’magnitude’

  The scale factor of uni-variate random noise applied to each of a robot’s given initial joint positions. Setting this value to “None” or 0.0 results in no noise being applied. If “gaussian” type of noise is applied then this magnitude scales the standard deviation applied, If “uniform” type of noise is applied then this magnitude sets the bounds of the sampling range

  ’type’

  Type of noise to apply. Can either specify “gaussian” or “uniform”

  Note

  Specifying None will automatically create the required dict with “magnitude” set to 0.0

• mount_type (str) – type of mount, used to instantiate mount models from mount factory. Default is “default”, which is the default mount associated with this robot’s corresponding model. None results in no mount, and any other (valid) model overrides the default mount.

• 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.

load_model()

Loads robot and optionally add grippers.

reset_sim(sim: mujoco_py.cymj.MjSim)

Replaces current sim with a new sim

Parameters

sim (MjSim) – New simulation being instantiated to replace the old one

reset(deterministic=False)

Sets initial pose of arm and grippers. Overrides robot joint configuration if we’re using a deterministic reset (e.g.: hard reset from xml file)

Parameters

deterministic (bool) – If true, will not randomize initializations within the sim

Raises

ValueError – [Invalid noise type]

setup_references()

Sets up necessary reference for robots, grippers, and objects.

setup_observables()

Sets up observables to be used for this robot

Returns

Dictionary mapping observable names to its corresponding Observable object

Return type

OrderedDict

control(action, policy_step=False)

Actuate the robot with the passed joint velocities and gripper control.

Parameters

• action (np.array) – The control to apply to the robot. The first @self.robot_model.dof dimensions should be the desired normalized joint velocities and if the robot has a gripper, the next @self.gripper.dof dimensions should be actuation controls for the gripper.

• policy_step (bool) – Whether a new policy step (action) is being taken

check_q_limits()

Check if this robot is either very close or at the joint limits

Returns

True if this arm is near its joint limits

Return type

bool

visualize(vis_settings)

Do any necessary visualization for this robot

Parameters

vis_settings (dict) – Visualization keywords mapped to T/F, determining whether that specific component should be visualized. Should have “robots” keyword as well as any other robot-specific options specified.

pose_in_base_from_name(name)

A helper function that takes in a named data field and returns the pose of that object in the base frame.

Parameters

name (str) – Name of body in sim to grab pose

Returns

(4,4) array corresponding to the pose of @name in the base frame

Return type

np.array

set_robot_joint_positions(jpos)

Helper method to force robot joint positions to the passed values.

Parameters

jpos (np.array) – Joint positions to manually set the robot to

get_sensor_measurement(sensor_name)

Grabs relevant sensor data from the sim object

Parameters

sensor_name (str) – name of the sensor

Returns

sensor values

Return type

np.array

property action_limits

Action lower/upper limits per dimension.

Returns

• (np.array) minimum (low) action values

• (np.array) maximum (high) action values

Return type

2-tuple

property torque_limits

Torque lower/upper limits per dimension.

Returns

• (np.array) minimum (low) torque values

• (np.array) maximum (high) torque values

Return type

2-tuple

property action_dim

Action space dimension for this robot

property dof

Returns: int: the active DoF of the robot (Number of robot joints + active gripper DoF).

property js_energy

Returns: np.array: the energy consumed by each joint between previous and current steps

property joint_indexes

Returns: list: mujoco internal indexes for the robot joints

property _joint_positions

Returns: np.array: joint positions (in angles / radians)

property _joint_velocities

Returns: np.array: joint velocities (angular velocity)

Initializes a manipulator robot simulation object, as defined by a single corresponding robot arm XML and associated gripper XML

grip_action(gripper, gripper_action)

Executes @gripper_action for specified @gripper

Parameters

• gripper (GripperModel) – Gripper to execute action for

• gripper_action (float) – Value between [-1,1] to send to gripper

property ee_ft_integral

Returns: float or dict: either single value or arm-specific entries specifying the integral over time of the applied

ee force-torque for that arm

property ee_force

Returns: np.array or dict: either single value or arm-specific entries specifying the force applied at the force sensor

at the robot arm’s eef

property ee_torque

Returns: np.array or dict: either single value or arm-specific entries specifying the torque applied at the torque

sensor at the robot arm’s eef

property _hand_pose

Returns: np.array or dict: either single value or arm-specific entries specifying the eef pose in base frame of

robot.

property _hand_quat

Returns: np.array or dict: either single value or arm-specific entries specifying the eef quaternion in base frame

of robot.

property _hand_total_velocity

Returns: np.array or dict: either single value or arm-specific entries specifying the total eef velocity

(linear + angular) in the base frame as a numpy array of shape (6,)

property _hand_pos

Returns: np.array or dict: either single value or arm-specific entries specifying the position of eef in base frame

of robot.

property _hand_orn

Returns: np.array or dict: either single value or arm-specific entries specifying the orientation of eef in base

frame of robot as a rotation matrix.

property _hand_vel

Returns: np.array or dict: either single value or arm-specific entries specifying the velocity of eef in base frame

of robot.

property _hand_ang_vel

Returns: np.array or dict: either single value or arm-specific entries specifying the angular velocity of eef in

base frame of robot.

Initializes a single-armed robot simulation object.

Parameters

• robot_type (str) – Specification for specific robot arm to be instantiated within this env (e.g: “Panda”)

• idn (int or str) – Unique ID of this robot. Should be different from others

• controller_config (dict) – If set, contains relevant controller parameters for creating a custom controller. Else, uses the default controller for this specific task

• initial_qpos (sequence of float) – If set, determines the initial joint positions of the robot to be instantiated for the task

• initialization_noise (dict) –

  Dict containing the initialization noise parameters. The expected keys and corresponding value types are specified below:

  ’magnitude’

  The scale factor of uni-variate random noise applied to each of a robot’s given initial joint positions. Setting this value to “None” or 0.0 results in no noise being applied. If “gaussian” type of noise is applied then this magnitude scales the standard deviation applied, If “uniform” type of noise is applied then this magnitude sets the bounds of the sampling range

  ’type’

  Type of noise to apply. Can either specify “gaussian” or “uniform”

  Note

  Specifying None will automatically create the required dict with “magnitude” set to 0.0

• mount_type (str) – type of mount, used to instantiate mount models from mount factory. Default is “default”, which is the default mount associated with this robot’s corresponding model. None results in no mount, and any other (valid) model overrides the default mount.

• gripper_type (str) – type of gripper, used to instantiate gripper models from gripper factory. Default is “default”, which is the default gripper associated within the ‘robot’ specification. None removes the gripper, and any other (valid) model overrides the default gripper

• 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.

control(action, policy_step=False)

Actuate the robot with the passed joint velocities and gripper control.

Parameters

• action (np.array) – The control to apply to the robot. The first @self.robot_model.dof dimensions should be the desired normalized joint velocities and if the robot has a gripper, the next @self.gripper.dof dimensions should be actuation controls for the gripper.

• policy_step (bool) – Whether a new policy step (action) is being taken

Raises

AssertionError – [Invalid action dimension]

property ee_ft_integral

Returns: np.array: the integral over time of the applied ee force-torque

property ee_force

Returns: np.array: force applied at the force sensor at the robot arm’s eef

property ee_torque

Returns torque applied at the torque sensor at the robot arm’s eef

property _hand_pose

Returns: np.array: (4,4) array corresponding to the eef pose in base frame of robot.

property _hand_quat

Returns: np.array: (x,y,z,w) eef quaternion in base frame of robot.

property _hand_total_velocity

Returns: np.array: 6-array representing the total eef velocity (linear + angular) in the base frame

property _hand_pos

Returns: np.array: 3-array representing the position of eef in base frame of robot.

property _hand_orn

Returns: np.array: (3,3) array representing the orientation of eef in base frame of robot as a rotation matrix.

property _hand_vel

Returns: np.array: (x,y,z) velocity of eef in base frame of robot.

property _hand_ang_vel

Returns: np.array: (ax,ay,az) angular velocity of eef in base frame of robot.

Initializes a bimanual robot simulation object.

Parameters

• robot_type (str) – Specification for specific robot arm to be instantiated within this env (e.g: “Panda”)

• idn (int or str) – Unique ID of this robot. Should be different from others

• controller_config (dict or list of dict --> dict of dict) –

  If set, contains relevant controller parameters for creating custom controllers. Else, uses the default controller for this specific task. Should either be single dict if same controller is to be used for both robot arms or else it should be a list of length 2.

  NOTE

  In the latter case, assumes convention of [right, left]

• initial_qpos (sequence of float) – If set, determines the initial joint positions of the robot to be instantiated for the task

• initialization_noise (dict) –

  Dict containing the initialization noise parameters. The expected keys and corresponding value types are specified below:

  ’magnitude’

  The scale factor of uni-variate random noise applied to each of a robot’s given initial joint positions. Setting this value to “None” or 0.0 results in no noise being applied. If “gaussian” type of noise is applied then this magnitude scales the standard deviation applied, If “uniform” type of noise is applied then this magnitude sets the bounds of the sampling range

  ’type’

  Type of noise to apply. Can either specify “gaussian” or “uniform”

  Note

  Specifying None will automatically create the required dict with “magnitude” set to 0.0

• mount_type (str) – type of mount, used to instantiate mount models from mount factory. Default is “default”, which is the default mount associated with this robot’s corresponding model. None results in no mount, and any other (valid) model overrides the default mount.

• gripper_type (str or list of str --> dict) –

  type of gripper, used to instantiate gripper models from gripper factory. Default is “default”, which is the default gripper associated within the ‘robot’ specification. None removes the gripper, and any other (valid) model overrides the default gripper. Should either be single str if same gripper type is to be used for both arms or else it should be a list of length 2

  NOTE

  In the latter case, assumes convention of [right, left]

• 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.

control(action, policy_step=False)

Actuate the robot with the passed joint velocities and gripper control.

Parameters

• action (np.array) –

  The control to apply to the robot. The first @self.robot_model.dof dimensions should be the desired normalized joint velocities and if the robot has a gripper, the next @self.gripper.dof dimensions should be actuation controls for the gripper.

  NOTE

  Assumes inputted actions are of form: [right_arm_control, right_gripper_control, left_arm_control, left_gripper_control]

• policy_step (bool) – Whether a new policy step (action) is being taken

Raises

AssertionError – [Invalid action dimension]

property ee_ft_integral

Returns: dict: each arm-specific entry specifies the integral over time of the applied ee force-torque for that arm

property ee_force

Returns: dict: each arm-specific entry specifies the force applied at the force sensor at the robot arm’s eef

property ee_torque

Returns: dict: each arm-specific entry specifies the torque applied at the torque sensor at the robot arm’s eef

property _hand_pose

Returns: dict: each arm-specific entry specifies the eef pose in base frame of robot.

property _hand_quat

Returns: dict: each arm-specific entry specifies the eef quaternion in base frame of robot.

property _hand_total_velocity

Returns: dict: each arm-specific entry specifies the total eef velocity (linear + angular) in the base frame as a numpy array of shape (6,)

property _hand_pos

Returns: dict: each arm-specific entry specifies the position of eef in base frame of robot.

property _hand_orn

Returns: dict: each arm-specific entry specifies the orientation of eef in base frame of robot as a rotation matrix.

property _hand_vel

Returns: dict: each arm-specific entry specifies the velocity of eef in base frame of robot.

property _hand_ang_vel

Returns: dict: each arm-specific entry specifies the angular velocity of eef in base frame of robot.