Extension - NLP interface: Low-level NLP formulation and solving

This is completely independent from all robotics code. Provides a generic interface to NLP formulation and calling various solvers.

import robotic as ry
import numpy as np

Define a function to compute differentiable features

#the function needs to have the signature (array) -> (array, array) with dimensionalities (n) -> (d, d-times-n)
def sqrPot(x):
    y = np.array(x)
    y[0] = y[0] - 1.
    J = np.eye(y.size)
    return y,J

Define a NLP (non-linear mathematical program)

nlp = ry.NLP_Factory()
nlp.setDimension(3)
nlp.setBounds([-2,-2,-2],[2,2,2])
nlp.setFeatureTypes([ry.OT.sos, ry.OT.sos, ry.OT.sos])
nlp.setEvalCallback(sqrPot)

Define a solver

solver = ry.NLP_Solver()
solver.setProblem(nlp)
solver.setSolver(ry.NLP_SolverID.newton)

solver.solve(True)

solver.getTrace_x()

solver.getTrace_costs()