control.controller

lsy_drone_racing.control.controller

Base class for controller implementations.

Your task is to implement your own controller. This class must be the parent class of your implementation. You have to use the same function signatures as defined by the base class. Apart from that, you are free to add any additional methods, attributes, or classes to your controller.

As an example, you could load the weights of a neural network in the constructor and use it to compute the control commands in the compute_control method. You could also use the step_callback method to update the controller state at runtime.

Note

You can only define one controller class in a single file. Otherwise we will not be able to determine which class to use.

Classes

Controller(obs, info, config)

Bases: ABC

Base class for controller implementations.

Initialization of the controller.

Instructions

The controller's constructor has access the initial observation obs, the a priori information contained in dictionary info, and the config of the race track. Use this method to initialize constants, counters, pre-plan trajectories, etc.

Parameters:

Name	Type	Description	Default
obs	dict[str, NDArray[floating]]	The initial observation of the environment's state. See the environment's observation space for details.	required
info	dict	The initial environment information from the reset.	required
config	dict	The race configuration. See the config files for details. Contains additional information such as disturbance configurations, randomizations, etc.	required

Source code in lsy_drone_racing/control/controller.py

def __init__(self, obs: dict[str, NDArray[np.floating]], info: dict, config: dict):
    """Initialization of the controller.

    Instructions:
        The controller's constructor has access the initial observation `obs`, the a priori
        information contained in dictionary `info`, and the config of the race track. Use this
        method to initialize constants, counters, pre-plan trajectories, etc.

    Args:
        obs: The initial observation of the environment's state. See the environment's
            observation space for details.
        info: The initial environment information from the reset.
        config: The race configuration. See the config files for details. Contains additional
            information such as disturbance configurations, randomizations, etc.
    """

Methods:

compute_control(obs, info=None) abstractmethod

Compute the next desired state of the drone.

Instructions

Implement this method to return the target state to be sent to the Crazyflie.

Parameters:

Name	Type	Description	Default
obs	dict[str, NDArray[floating]]	The current observation of the environment. See the environment's observation space for details.	required
info	dict | None	Optional additional information as a dictionary.	None

Returns:

Type	Description
NDArray[floating]	A drone state command [x, y, z, vx, vy, vz, ax, ay, az, yaw, rrate, prate, yrate] in
NDArray[floating]	absolute coordinates or an attitude command [thrust, roll, pitch, yaw] as a numpy array.

Source code in lsy_drone_racing/control/controller.py

@abstractmethod
def compute_control(
    self, obs: dict[str, NDArray[np.floating]], info: dict | None = None
) -> NDArray[np.floating]:
    """Compute the next desired state of the drone.

    Instructions:
        Implement this method to return the target state to be sent to the Crazyflie.

    Args:
        obs: The current observation of the environment. See the environment's observation space
            for details.
        info: Optional additional information as a dictionary.

    Returns:
        A drone state command [x, y, z, vx, vy, vz, ax, ay, az, yaw, rrate, prate, yrate] in
        absolute coordinates or an attitude command [thrust, roll, pitch, yaw] as a numpy array.
    """

episode_callback()

Callback function called once after each episode.

You can use this function to reset your controller's internal state, save training data, train your models, compute additional statistics, etc.

Instructions

Use any collected information to learn, adapt, and/or re-plan.

Source code in lsy_drone_racing/control/controller.py

def episode_callback(self):
    """Callback function called once after each episode.

    You can use this function to reset your controller's internal state, save training data,
    train your models, compute additional statistics, etc.

    Instructions:
        Use any collected information to learn, adapt, and/or re-plan.
    """

episode_reset()

Reset the controller's internal state and models if necessary.

Source code in lsy_drone_racing/control/controller.py

def episode_reset(self):
    """Reset the controller's internal state and models if necessary."""

render_callback(sim)

Callback function called before the environment's rendering.

You can use this function to render additional information on the screen, such as the planned trajectory, the drone's target state, etc.

Source code in lsy_drone_racing/control/controller.py

def render_callback(self, sim: Sim):
    """Callback function called before the environment's rendering.

    You can use this function to render additional information on the screen, such as the
    planned trajectory, the drone's target state, etc.
    """

reset()

Reset internal variables if necessary.

Source code in lsy_drone_racing/control/controller.py

def reset(self):
    """Reset internal variables if necessary."""

step_callback(action, obs, reward, terminated, truncated, info)

Callback function called once after the control step.

You can use this function to update your controller's internal state, save training data, update your models, and to terminate the episode.

Instructions

Use any collected information to learn, adapt, and/or re-plan.

Parameters:

Name	Type	Description	Default
action	NDArray[floating]	Latest applied action.	required
obs	dict[str, NDArray[floating]]	Latest environment observation.	required
reward	float	Latest reward.	required
terminated	bool	Latest terminated flag.	required
truncated	bool	Latest truncated flag.	required
info	dict	Latest information dictionary.	required

Returns:

Type	Description
bool	A flag to signal if the controller has finished.

Source code in lsy_drone_racing/control/controller.py

def step_callback(
    self,
    action: NDArray[np.floating],
    obs: dict[str, NDArray[np.floating]],
    reward: float,
    terminated: bool,
    truncated: bool,
    info: dict,
) -> bool:
    """Callback function called once after the control step.

    You can use this function to update your controller's internal state, save training data,
    update your models, and to terminate the episode.

    Instructions:
        Use any collected information to learn, adapt, and/or re-plan.

    Args:
        action: Latest applied action.
        obs: Latest environment observation.
        reward: Latest reward.
        terminated: Latest terminated flag.
        truncated: Latest truncated flag.
        info: Latest information dictionary.

    Returns:
        A flag to signal if the controller has finished.
    """
    return True  # Does not finish by default