upkie.envs.wrappers.add_lag_to_action.AddLagToAction Class Reference

Model lag by applying a low-pass filter to the action of an environment. More...

Public Member Functions
def	__init__ (self, env, Union[float, gym.spaces.Box] time_constant)
	Initialize wrapper. More...
def	reset (self, **kwargs)
	Reset the environment. More...
Tuple[np.ndarray, float, bool, bool, dict]	step (self, np.ndarray action)
	Step the environment. More...

Public Attributes
	filtered_action
	Wrapped action after low-pass filtering.
	time_constant
	Cutoff period in seconds of a low-pass filter applied to the action.
	time_constant_box
	Box space from which the time constant is sampled at every reset of the environment.

Detailed Description

Model lag by applying a low-pass filter to the action of an environment.

Note that there is a difference between "delay" and "lag":

• Delay is a fixed time interval corresponding to the time it takes the input to affect the output, e.g. output(t + delay) = input(t).
• Lag is a phase shift in the system's response. It can be thought of as a gradual response to input changes where the output does not immediately match the input, e.g. d/dt{output}(t) = lag * (input(t) - output(t)).

In this wrapper, we model lag where the output (action forward to the wrapped environment) is a low-pass filtered version of the input (action passed to step).

Constructor & Destructor Documentation

__init__()

def upkie.envs.wrappers.add_lag_to_action.AddLagToAction.__init__	(		self,
			env,
		Union[float, gym.spaces.Box]	time_constant
	)

Initialize wrapper.

Parameters

env	Environment to wrap.
time_constant	Cutoff period in seconds of the low-pass filter applied to the action. If a Box is provided, couple of lower and upper bounds for the action: a new time constant is sampled uniformly at random between these bounds at every reset of the environment.

Member Function Documentation

reset()

def upkie.envs.wrappers.add_lag_to_action.AddLagToAction.reset	(		self,
		**	kwargs
	)

Reset the environment.

Parameters

kwargs

Keyword arguments forwarded to the wrapped environment.

step()

Tuple[np.ndarray, float, bool, bool, dict] upkie.envs.wrappers.add_lag_to_action.AddLagToAction.step	(		self,
		np.ndarray	action
	)

Step the environment.

Parameters

action

Action from the agent.

Returns

Tuple with (observation, reward, terminated, truncated,info). See upkie.envs.upkie_base_env.UpkieBaseEnv.step for details.

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The documentation for this class was generated from the following file:

• upkie/envs/wrappers/add_lag_to_action.py