movement_primitives.dmp.DMPWithFinalVelocity¶
- class movement_primitives.dmp.DMPWithFinalVelocity(n_dims, execution_time=1.0, dt=0.01, n_weights_per_dim=10, int_dt=0.001, p_gain=0.0)¶
Bases:
WeightParametersMixin,DMPBaseDynamical movement primitive (DMP) with final velocity.
Equation of transformation system (according to [1], Eq. 6):
\[\ddot{y} = (\alpha_y (\beta_y (g - y) + \tau\dot{g} - \tau \dot{y}) + f(z))/\tau^2\]- Parameters:
- n_dimsint
State space dimensions.
- execution_timefloat, optional (default: 1)
Execution time of the DMP: \(\tau\).
- dtfloat, optional (default: 0.01)
Time difference between DMP steps: \(\Delta t\).
- n_weights_per_dimint, optional (default: 10)
Number of weights of the function approximator per dimension.
- int_dtfloat, optional (default: 0.001)
Time difference for Euler integration.
- p_gainfloat, optional (default: 0)
Gain for proportional controller of DMP tracking error. The domain is [0, execution_time**2/dt].
References
[1]Muelling, K., Kober, J., Kroemer, O., Peters, J. (2013). Learning to Select and Generalize Striking Movements in Robot Table Tennis. International Journal of Robotics Research 32 (3), 263-279. https://www.ias.informatik.tu-darmstadt.de/uploads/Publications/Muelling_IJRR_2013.pdf
- Attributes:
- execution_time_float
Execution time of the DMP.
- dt_float
Time difference between DMP steps. This value can be changed to adapt the frequency.
Methods
configure([t, start_y, start_yd, start_ydd, ...])Set meta parameters.
Get weight vector of DMP.
imitate(T, Y[, regularization_coefficient])Imitate demonstration.
n_steps_open_loop(last_y, last_yd, n_steps)Perform 'n_steps' steps.
open_loop([run_t, coupling_term])Run DMP open loop.
reset()Reset DMP to initial state and time.
set_weights(weights)Set weight vector of DMP.
step(last_y, last_yd[, coupling_term])DMP step.
get_execution_time_
set_execution_time_
- __init__(n_dims, execution_time=1.0, dt=0.01, n_weights_per_dim=10, int_dt=0.001, p_gain=0.0)¶
Methods
__init__(n_dims[, execution_time, dt, ...])configure([t, start_y, start_yd, start_ydd, ...])Set meta parameters.
get_execution_time_()Get weight vector of DMP.
imitate(T, Y[, regularization_coefficient])Imitate demonstration.
n_steps_open_loop(last_y, last_yd, n_steps)Perform 'n_steps' steps.
open_loop([run_t, coupling_term])Run DMP open loop.
reset()Reset DMP to initial state and time.
set_execution_time_(execution_time)set_weights(weights)Set weight vector of DMP.
step(last_y, last_yd[, coupling_term])DMP step.
Attributes
execution_time_Total number of weights configuring the forcing term.
- configure(t=None, start_y=None, start_yd=None, start_ydd=None, goal_y=None, goal_yd=None, goal_ydd=None)¶
Set meta parameters.
- Parameters:
- tfloat, optional
Time at current step.
- start_yarray, shape (n_dims,)
Initial state.
- start_ydarray, shape (n_vel_dims,)
Initial velocity.
- start_yddarray, shape (n_vel_dims,)
Initial acceleration.
- goal_yarray, shape (n_dims,)
Goal state.
- goal_ydarray, shape (n_vel_dims,)
Goal velocity.
- goal_yddarray, shape (n_vel_dims,)
Goal acceleration.
- get_weights()¶
Get weight vector of DMP.
- Returns:
- weightsarray, shape (N * n_weights_per_dim,)
Current weights of the DMP. N depends on the type of DMP
- imitate(T, Y, regularization_coefficient=0.0)¶
Imitate demonstration.
- Parameters:
- Tarray, shape (n_steps,)
Time for each step.
- Yarray, shape (n_steps, n_dims)
State at each step.
- regularization_coefficientfloat, optional (default: 0)
Regularization coefficient for regression.
- n_steps_open_loop(last_y, last_yd, n_steps)¶
Perform ‘n_steps’ steps.
- Parameters:
- last_yarray, shape (n_dims,)
Last state.
- last_ydarray, shape (n_dims,)
Last time derivative of state (e.g., velocity).
- n_stepsint
Number of steps.
- Returns:
- yarray, shape (n_dims,)
Next state.
- ydarray, shape (n_dims,)
Next time derivative of state (e.g., velocity).
- property n_weights¶
Total number of weights configuring the forcing term.
- open_loop(run_t=None, coupling_term=None)¶
Run DMP open loop.
- Parameters:
- run_tfloat, optional (default: execution_time)
Run time of DMP. Can be shorter or longer than execution_time.
- coupling_termobject, optional (default: None)
Coupling term that will be added to velocity.
- Returns:
- Tarray, shape (n_steps,)
Time for each step.
- Yarray, shape (n_steps, n_dims)
State at each step.
- reset()¶
Reset DMP to initial state and time.
- set_weights(weights)¶
Set weight vector of DMP.
- Parameters:
- weightsarray, shape (N * n_weights_per_dim,)
New weights of the DMP. N depends on the type of DMP
- step(last_y, last_yd, coupling_term=None)¶
DMP step.
- Parameters:
- last_yarray, shape (n_dims,)
Last state.
- last_ydarray, shape (n_dims,)
Last time derivative of state (e.g., velocity).
- coupling_termobject, optional (default: None)
Coupling term that will be added to velocity.
- Returns:
- yarray, shape (n_dims,)
Next state.
- ydarray, shape (n_dims,)
Next time derivative of state (e.g., velocity).