trajectory module

class dynamapp.trajectory.Trajectory(n: int, sampling: int, ti: float, tf: float)

Bases: ABC

Base class for trajectory motion generation.

abstract get_value(t: float)

abstract compute_with_constraints(qmin, qmax, qpmin, qpmax, qppmin, qppmax)

abstract compute_full_trajectory()

class dynamapp.trajectory.SplineTrajectory(ndof, sampling, ti, tf, control_points)

Bases: Trajectory

Spline-based trajectory.

Todo

Implement the compute_with_constraints function

get_value(t: float)

compute_full_trajectory()

compute_with_constraints(qmin, qmax, qpmin, qpmax, qppmin, qppmax)

class dynamapp.trajectory.TrapezoidalTrajectory(n, sampling, ti, tf, q0, qf, acc, vel)

Bases: Trajectory

Trapezoidal velocity profile trajectory.

Todo

Implment the compute_with_constraints function

get_value(t: float)

compute_full_trajectory()

compute_with_constraints(qmin, qmax, qpmin, qpmax, qppmin, qppmax)

class dynamapp.trajectory.PeriodicTrajectory(n, sampling, ti, tf, frequency, Aij, Bij, nb_terms)

Bases: Trajectory

Periodic trajectory based on Fourier series.[1]

Todo

Implment the compute_with_constraints function

Ref:

• [1] Fourier-based optimal excitation trajectories for the dynamic

identification of robots, Kyung.Jo Park - Robotica - 2006.

get_value(t: float)

compute_full_trajectory()

compute_with_constraints(qmin, qmax, qpmin, qpmax, qppmin, qppmax)

class dynamapp.trajectory.StepTrajectory(ndof, sampling, ti, tf, epsilon, amplitude)

Bases: Trajectory

Step trajectory with fixed small duration epsilon and given amplitude.

Todo

Implment the compute_with_constraints function

get_value(t: float)

compute_full_trajectory() → jax.numpy.array

compute_with_constraints(qmin, qmax, qpmin, qpmax, qppmin, qppmax)