inverse-kinematics.py

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from __future__ import print_function

import numpy as np
from numpy.linalg import norm, solve

import pinocchio

model = pinocchio.buildSampleModelManipulator()
data  = model.createData()

JOINT_ID = 6
oMdes = pinocchio.SE3(np.eye(3), np.array([1.0, 0.0, 1.0]))

q      = pinocchio.neutral(model)
eps    = 1e-4
IT_MAX = 1000
DT     = 1e-1
damp   = 1e-12

i=0
while True:
    pinocchio.forwardKinematics(model,data,q)
    iMd = data.oMi[JOINT_ID].actInv(oMdes)
    err = pinocchio.log(iMd).vector  # in joint frame
    if norm(err) < eps:
        success = True
        break
    if i >= IT_MAX:
        success = False
        break
    J = pinocchio.computeJointJacobian(model,data,q,JOINT_ID)  # in joint frame
    J = -np.dot(pinocchio.Jlog6(iMd.inverse()), J)
    v = - J.T.dot(solve(J.dot(J.T) + damp * np.eye(6), err))
    q = pinocchio.integrate(model,q,v*DT)
    if not i % 10:
        print('%d: error = %s' % (i, err.T))
    i += 1

if success:
    print("Convergence achieved!")
else:
    print("\nWarning: the iterative algorithm has not reached convergence to the desired precision")

print('\nresult: %s' % q.flatten().tolist())
print('\nfinal error: %s' % err.T)