did some cartesian control

script/controller.py

@@ -0,0 +1,90 @@
+#! /usr/bin/env python
+"""Controller should execute control for a given effector"""
+import os
+
+# import rospy
+import numpy as np
+from naoqi import ALProxy
+
+
+FRAME_TORSO = 0
+K = 0.1
+mp = ALProxy('ALMotion', os.environ['NAO_IP'], 9559)
+mp.wakeUp()
+
+
+def _get_transform(joint):
+    return np.array(
+        mp.getTransform(joint, FRAME_TORSO, False)
+    ).reshape((4, 4))
+
+
+def _xyz(joint):
+    return np.array(mp.getPosition(joint, FRAME_TORSO, False))[:3]
+
+
+def jacobian():
+    # get current positions
+    # according to control figure these values should actually come
+    # from the integration step in the previous first control loop
+
+    end_position = _xyz('LArm')
+    shoulder_position = _xyz('LShoulderPitch')
+    bicep_position = _xyz('LShoulderRoll')
+    elbow_position = _xyz('LElbowYaw')
+    forearm_position = _xyz('LElbowRoll')
+
+    # get transformed rotation axes, transformation to torso frame
+
+    x_axis = np.array([[1, 0, 0, 1]]).T
+    y_axis = np.array([[0, 1, 0, 1]]).T
+    z_axis = np.array([[0, 0, 1, 1]]).T
+
+    shoulder_axis = _get_transform('LShoulderPitch').dot(y_axis)
+    bicep_axis = _get_transform('LShoulderRoll').dot(z_axis)
+    elbow_axis = _get_transform('LElbowYaw').dot(x_axis)
+    forearm_axis = _get_transform('LElbowRoll').dot(z_axis)
+
+    xyzs = np.array([shoulder_position, bicep_position, elbow_position,
+                     forearm_position])
+
+    axes = np.concatenate(
+        [shoulder_axis, bicep_axis, elbow_axis, forearm_axis],
+        axis=1
+    )[:3].T
+
+    # get basis vectors of jacobian
+
+    jacobian = np.cross(axes, end_position - xyzs).T
+
+    # shoulder_basis = np.cross(shoulder_axis[:3].flatten(),
+                              # end_position - shoulder_position)
+    # bicep_basis = np.cross(bicep_axis[:3].flatten(),
+                           # end_position - bicep_position)
+    # elbow_basis = np.cross(elbow_axis[:3].flatten(),
+                           # end_position - elbow_position)
+    # forearm_basis = np.cross(forearm_axis[:3].flatten(),
+                             # end_position - forearm_position)
+
+    # build jacobian matrix
+    # jacobian = np.concatenate(
+        # [shoulder_basis, bicep_basis, elbow_basis, forearm_basis],
+        # axis=0
+    # ).T
+
+    return jacobian
+
+
+def pseudo_inverse(jacobian):
+    return np.linalg.pinv(jacobian)
+
+
+def reference_generator(xyz):
+    delta = K * (xyz - _xyz('LArm'))
+    return np.linalg.pinv(jacobian()).dot(delta).flatten()
+
+
+def movement(xyz):
+    ref = reference_generator(np.array(xyz)).tolist()
+    mp.changeAngles(['LShoulderPitch', 'LShoulderRoll',
+                     'LElbowYaw', 'LElbowRoll'], ref, 0.2)