robosuite.controllers.parts.mobile_base package

robosuite.controllers.parts.mobile_base package#

Submodules#

robosuite.controllers.parts.mobile_base.joint_vel module#

class robosuite.controllers.parts.mobile_base.joint_vel.LegacyMobileBaseJointVelocityController(*args, **kwargs)#

Bases: MobileBaseJointVelocityController

Legacy version of MobileBaseJointVelocityController, created to address the recent change in the axis of the forward joint in the mobile base xml. This controller is identical to the original MobileBaseJointVelocityController, except that it dynamically checks the axis of the forward joint and reorders the input action accordingly if the forward axis is the y axis instead of the x axis. This allows for backwards compatibility with previously collected datasets that were generated using older versions of the mobile base xml.

set_goal(action, set_qpos=None)#

Sets goal based on input @action. If self.impedance_mode is not “fixed”, then the input will be parsed into the delta values to update the goal position / pose and the kp and/or damping_ratio values to be immediately updated internally before executing the proceeding control loop.

Note that @action expected to be in the following format, based on impedance mode!

Mode ‘fixed’:

[joint pos command]

Mode ‘variable’:

[damping_ratio values, kp values, joint pos command]

Mode ‘variable_kp’:

[kp values, joint pos command]

Parameters:

  • action (Iterable) – Desired relative joint position goal state

  • set_qpos (Iterable) – If set, overrides @action and sets the desired absolute joint position goal state

Raises:

AssertionError – [Invalid action dimension size]

class robosuite.controllers.parts.mobile_base.joint_vel.MobileBaseJointVelocityController(sim, joint_indexes, actuator_range, input_max=1, input_min=-1, output_max=1, output_min=-1, kp=50, damping_ratio=1, impedance_mode='fixed', kp_limits=(0, 300), damping_ratio_limits=(0, 100), policy_freq=20, qpos_limits=None, interpolator=None, **kwargs)#

Bases: MobileBaseController

Controller for controlling robot arm via impedance control. Allows position control of the robot’s joints.

NOTE: Control input actions assumed to be taken relative to the current joint positions. A given action to this controller is assumed to be of the form: (dpos_j0, dpos_j1, … , dpos_jn-1) for an n-joint robot

Parameters:

  • sim (MjSim) – Simulator instance this controller will pull robot state updates from

  • joint_indexes (dict) –

    Each key contains sim reference indexes to relevant robot joint information, namely:

    ’joints’:

    list of indexes to relevant robot joints

    ’qpos’:

    list of indexes to relevant robot joint positions

    ’qvel’:

    list of indexes to relevant robot joint velocities

  • actuator_range (2-tuple of array of float) – 2-Tuple (low, high) representing the robot joint actuator range

  • input_max (float or Iterable of float) – Maximum above which an inputted action will be clipped. Can be either be a scalar (same value for all action dimensions), or a list (specific values for each dimension). If the latter, dimension should be the same as the control dimension for this controller

  • input_min (float or Iterable of float) – Minimum below which an inputted action will be clipped. Can be either be a scalar (same value for all action dimensions), or a list (specific values for each dimension). If the latter, dimension should be the same as the control dimension for this controller

  • output_max (float or Iterable of float) – Maximum which defines upper end of scaling range when scaling an input action. Can be either be a scalar (same value for all action dimensions), or a list (specific values for each dimension). If the latter, dimension should be the same as the control dimension for this controller

  • output_min (float or Iterable of float) – Minimum which defines upper end of scaling range when scaling an input action. Can be either be a scalar (same value for all action dimensions), or a list (specific values for each dimension). If the latter, dimension should be the same as the control dimension for this controller

  • kp (float or Iterable of float) – positional gain for determining desired torques based upon the joint pos error. Can be either be a scalar (same value for all action dims), or a list (specific values for each dim)

  • damping_ratio (float or Iterable of float) – used in conjunction with kp to determine the velocity gain for determining desired torques based upon the joint pos errors. Can be either be a scalar (same value for all action dims), or a list (specific values for each dim)

  • impedance_mode (str) – Impedance mode with which to run this controller. Options are {“fixed”, “variable”, “variable_kp”}. If “fixed”, the controller will have fixed kp and damping_ratio values as specified by the @kp and @damping_ratio arguments. If “variable”, both kp and damping_ratio will now be part of the controller action space, resulting in a total action space of num_joints * 3. If “variable_kp”, only kp will become variable, with damping_ratio fixed at 1 (critically damped). The resulting action space will then be num_joints * 2.

  • kp_limits (2-list of float or 2-list of Iterable of floats) – Only applicable if @impedance_mode is set to either “variable” or “variable_kp”. This sets the corresponding min / max ranges of the controller action space for the varying kp values. Can be either be a 2-list (same min / max for all kp action dims), or a 2-list of list (specific min / max for each kp dim)

  • damping_ratio_limits (2-list of float or 2-list of Iterable of floats) – Only applicable if @impedance_mode is set to “variable”. This sets the corresponding min / max ranges of the controller action space for the varying damping_ratio values. Can be either be a 2-list (same min / max for all damping_ratio action dims), or a 2-list of list (specific min / max for each damping_ratio dim)

  • policy_freq (int) – Frequency at which actions from the robot policy are fed into this controller

  • qpos_limits (2-list of float or 2-list of Iterable of floats) – Limits (rad) below and above which the magnitude of a calculated goal joint position will be clipped. Can be either be a 2-list (same min/max value for all joint dims), or a 2-list of list (specific min/max values for each dim)

  • interpolator (Interpolator) – Interpolator object to be used for interpolating from the current joint position to the goal joint position during each timestep between inputted actions

  • **kwargs – Does nothing; placeholder to “sink” any additional arguments so that instantiating this controller via an argument dict that has additional extraneous arguments won’t raise an error

Raises:

AssertionError – [Invalid impedance mode]

property control_limits#

Returns the limits over this controller’s action space, overrides the superclass property Returns the following (generalized for both high and low limits), based on the impedance mode:

Mode ‘fixed’:

[joint pos command]

Mode ‘variable’:

[damping_ratio values, kp values, joint pos command]

Mode ‘variable_kp’:

[kp values, joint pos command]

Returns:

  • (np.array) minimum action values

  • (np.array) maximum action values

Return type:

2-tuple

property name#

Name of this controller

Returns:

controller name

Return type:

str

reset_goal()#

Resets joint position goal to be current position

run_controller()#

Calculates the torques required to reach the desired setpoint

Returns:

Command torques

Return type:

np.array

set_goal(action, set_qpos=None)#

Sets goal based on input @action. If self.impedance_mode is not “fixed”, then the input will be parsed into the delta values to update the goal position / pose and the kp and/or damping_ratio values to be immediately updated internally before executing the proceeding control loop.

Note that @action expected to be in the following format, based on impedance mode!

Mode ‘fixed’:

[joint pos command]

Mode ‘variable’:

[damping_ratio values, kp values, joint pos command]

Mode ‘variable_kp’:

[kp values, joint pos command]

Parameters:

  • action (Iterable) – Desired relative joint position goal state

  • set_qpos (Iterable) – If set, overrides @action and sets the desired absolute joint position goal state

Raises:

AssertionError – [Invalid action dimension size]

robosuite.controllers.parts.mobile_base.mobile_base_controller module#

class robosuite.controllers.parts.mobile_base.mobile_base_controller.MobileBaseController(sim, joint_indexes, actuator_range, naming_prefix=None)#

Bases: object

General controller interface.

Requires reference to mujoco sim object, relevant joint_indexes to that robot, and whether an initial_joint is used for nullspace torques or not

Parameters:

  • sim (MjSim) – Simulator instance this controller will pull robot state updates from

  • joint_indexes (dict) –

    Each key contains sim reference indexes to relevant robot joint information, namely:

    ’joints’:

    list of indexes to relevant robot joints

    ’qpos’:

    list of indexes to relevant robot joint positions

    ’qvel’:

    list of indexes to relevant robot joint velocities

  • actuator_range (2-tuple of array of float) – 2-Tuple (low, high) representing the robot joint actuator range

property actuator_limits#

Torque limits for this controller

Returns:

  • (np.array) minimum actuator torques

  • (np.array) maximum actuator torques

Return type:

2-tuple

clip_torques(torques)#

Clips the torques to be within the actuator limits

Parameters:

torques (Iterable) – Torques to clip

Returns:

Clipped torques

Return type:

np.array

property control_limits#

Limits over this controller’s action space, which defaults to input min/max

Returns:

  • (np.array) minimum action values

  • (np.array) maximum action values

Return type:

2-tuple

get_base_pose()#
property name#

Name of this controller

Returns:

controller name

Return type:

str

static nums2array(nums, dim)#

Convert input @nums into numpy array of length @dim. If @nums is a single number, broadcasts it to the corresponding dimension size @dim before converting into a numpy array

Parameters:

  • nums (numeric or Iterable) – Either single value or array of numbers

  • dim (int) – Size of array to broadcast input to env.sim.data.actuator_force

Returns:

Array filled with values specified in @nums

Return type:

np.array

reset()#
reset_goal()#

Resets the goal – usually by setting to the goal to all zeros, but in some cases may be different (e.g.: OSC)

abstractmethod run_controller()#

Abstract method that should be implemented in all subclass controllers, and should convert a given action into torques (pre gravity compensation) to be executed on the robot. Additionally, resets the self.new_update flag so that the next self.update call will occur

scale_action(action)#

Clips @action to be within self.input_min and self.input_max, and then re-scale the values to be within the range self.output_min and self.output_max

Parameters:

action (Iterable) – Actions to scale

Returns:

Re-scaled action

Return type:

np.array

property torque_compensation#

Gravity compensation for this robot arm

Returns:

torques

Return type:

np.array

update(force=False)#

Updates the state of the robot arm, including end effector pose / orientation / velocity, joint pos/vel, jacobian, and mass matrix. By default, since this is a non-negligible computation, multiple redundant calls will be ignored via the self.new_update attribute flag. However, if the @force flag is set, the update will occur regardless of that state of self.new_update. This base class method of @run_controller resets the self.new_update flag

Parameters:

force (bool) – Whether to force an update to occur or not

update_initial_joints(initial_joints)#

Updates the internal attribute self.initial_joints. This is useful for updating changes in controller-specific behavior, such as with OSC where self.initial_joints is used for determine nullspace actions

This function can also be extended by subclassed controllers for additional controller-specific updates

Parameters:

initial_joints (Iterable) – Array of joint position values to update the initial joints

Module contents#

Contents