pyrcf.components.controller_manager
===================================

.. py:module:: pyrcf.components.controller_manager

.. autoapi-nested-parse::

   Defines controller managers that can be used to handle multiple controllers
   in the control loop.



Subpackages
-----------

.. toctree::
   :maxdepth: 1

   /autoapi/pyrcf/components/controller_manager/command_accumulators/index


Submodules
----------

.. toctree::
   :maxdepth: 1

   /autoapi/pyrcf/components/controller_manager/controller_manager_base/index
   /autoapi/pyrcf/components/controller_manager/simple_controller_manager/index


Classes
-------

.. autoapisummary::

   pyrcf.components.controller_manager.ControllerManagerBase
   pyrcf.components.controller_manager.SimpleControllerManager


Package Contents
----------------

.. py:class:: ControllerManagerBase(agents: List[pyrcf.components.agents.agent_base.AgentBase], command_accumulation_policy: pyrcf.components.controller_manager.command_accumulators.cmd_accumulation_policies.CommandAccumulatorBase)

   Bases: :py:obj:`abc.ABC`


   Base class for writing controller (agent) managers.


   .. py:attribute:: agents


   .. py:attribute:: _accumulator


   .. py:method:: add_agent(agent: pyrcf.components.agents.agent_base.AgentBase)

      Add an agent to be managed by this controller manager.

      :param agent: The agent to be added to the end of the list.
      :type agent: AgentBase

      :returns:

                The self object with the new agent added.
                    This is for using this method in a builder strategy.
      :rtype: ControllerManagerBase



   .. py:method:: set_cmd_accumulation_policy(policy: pyrcf.components.controller_manager.command_accumulators.cmd_accumulation_policies.CommandAccumulatorBase)

      Set/change the command accumulation policy for this mananger.

      :param policy: The new policy to be used.
      :type policy: CommandAccumulatorBase

      :returns:

                The self object with the policy updated.
                    This is for using this method in a builder strategy.
      :rtype: ControllerManagerBase



   .. py:method:: update(robot_state: pyrcf.core.types.RobotState, global_plan: pyrcf.core.types.GlobalMotionPlan, t: float, dt: float) -> pyrcf.core.types.RobotCmd
      :abstractmethod:


      Run one update step of all the 'agents' managed by this manager.

      :param robot_state: Current robot state. This is equivalent to 'observation' in
                          standard learning-based agents.
      :type robot_state: RobotState
      :param global_plan: The reference global plan to follow.
      :type global_plan: GlobalMotionPlan
      :param t: the current time signature of the control loop. Defaults to None
                (controllers may or may not need this).
      :type t: float, optional
      :param dt: the time since the last control loop. Defaults to None
                 (controllers may or may not need this).
      :type dt: float, optional

      :returns:

                The output control command (action) to be sent to the robot based on the
                    accumulation policy used by this manager.
      :rtype: RobotCmd

      :raises NotImplementedError: Raised if this method is not implemented by the child class.



   .. py:method:: shutdown()

      Cleanly shutdown all agents managed by this controller manager.



.. py:class:: SimpleControllerManager(agents: List[pyrcf.components.agents.agent_base.AgentBase] = None, command_accumulation_policy: pyrcf.components.controller_manager.command_accumulators.cmd_accumulation_policies.CommandAccumulatorBase = SimpleCmdOverride())

   Bases: :py:obj:`pyrcf.components.controller_manager.controller_manager_base.ControllerManagerBase`


   A simple controller manager that naively performs sequential updates of all agents it
   manages.


   .. py:method:: update(robot_state: pyrcf.core.types.RobotState, global_plan: pyrcf.core.types.GlobalMotionPlan, t: float, dt: float) -> pyrcf.core.types.RobotCmd

      Run one update step of all the 'agents' managed by this manager.

      :param robot_state: Current robot state. This is equivalent to 'observation' in
                          standard learning-based agents.
      :type robot_state: RobotState
      :param global_plan: The reference global plan to follow.
      :type global_plan: GlobalMotionPlan
      :param t: the current time signature of the control loop. Defaults to None
                (controllers may or may not need this).
      :type t: float, optional
      :param dt: the time since the last control loop. Defaults to None
                 (controllers may or may not need this).
      :type dt: float, optional

      :returns:

                The output control command (action) to be sent to the robot based on the
                    accumulation policy used by this manager.
      :rtype: RobotCmd

      :raises NotImplementedError: Raised if this method is not implemented by the child class.