예제 #1
0
    def CalcPoseError(self, X_WE_desired, q):
        pose = self.ForwardKinematics(q)
        err_vec = np.zeros(6)
        err_vec[-3:] = X_WE_desired.translation() - pose.translation()

        rot_err = AngleAxis(X_WE_desired.rotation() *
                            pose.rotation().transpose())
        err_vec[:3] = rot_err.axis() * rot_err.angle()
예제 #2
0
    def _revolute_feedback(self, joint, feedback):
        if feedback.event_type != InteractiveMarkerFeedback.POSE_UPDATE:
            return

        expected_frame = joint.child_body().body_frame().name()

        if expected_frame != feedback.header.frame_id:
            # TODO(sloretz) fix tf2_geometry_msgs_py :(
            # transformed_point = self._tf_buffer.transform(point_stamped, self._frame_id)
            print("TODO accept feedback in different frame")
            return

        qw = feedback.pose.orientation.w
        qx = feedback.pose.orientation.x
        qy = feedback.pose.orientation.y
        qz = feedback.pose.orientation.z

        new_orientation = Quaternion(qw, qx, qy, qz)
        prev_orientation = self._joint_prev_orientation[joint.name()]
        orientation_diff = prev_orientation.inverse().multiply(new_orientation)
        diff_aa = AngleAxis(orientation_diff)

        joint_axis = self._joint_axis_in_child[joint.name()]
        dot = numpy.dot(joint_axis, diff_aa.axis())
        if dot > 0.999:
            angle_inc = diff_aa.angle()
        elif dot < -0.999:
            angle_inc = -1 * diff_aa.angle()
        else:
            angle_inc = 0.

        angle = self._joint_states[self._joint_indexes[joint.name()]] + angle_inc

        if angle > joint.position_upper_limit():
            angle = joint.position_upper_limit()
        elif angle < joint.position_lower_limit():
            angle = joint.position_lower_limit()

        self._joint_states[self._joint_indexes[joint.name()]] = angle
        self._joint_prev_orientation[joint.name()] = new_orientation
예제 #3
0
def rotation_matrix_to_axang3(R):
    assert isinstance(R, RotationMatrix), repr(type(R))
    axang = AngleAxis(R.matrix())
    axang3 = axang.angle() * axang.axis()
    return axang3
    def DoCalcAbstractOutput(self, context, y_data):
        self.callback_lock.acquire()

        if self.selected_body and self.grab_in_progress:
            # Simple inverse dynamics PD rule to drive object to desired pose.
            body = self.selected_body

            # Load in robot state
            x_in = self.EvalVectorInput(context, 1).get_value()
            self.mbp.SetPositionsAndVelocities(self.mbp_context, x_in)
            TF_object = self.mbp.EvalBodyPoseInWorld(self.mbp_context, body)
            xyz = TF_object.translation()
            R = TF_object.rotation().matrix()
            TFd_object = self.mbp.EvalBodySpatialVelocityInWorld(
                self.mbp_context, body)
            xyzd = TFd_object.translational()
            Rd = TFd_object.rotational()

            # Match the object position directly to the hydra position.
            xyz_desired = self.desired_pose_in_world_frame.translation()

            # Regress xyz back to just the hydra pose in the attraction case
            if self.previously_freezing_rotation != self.freeze_rotation:
                self.selected_body_init_offset = TF_object
                self.grab_update_hydra_pose = RigidTransform(
                    self.desired_pose_in_world_frame)
            self.previously_freezing_rotation = self.freeze_rotation
            if self.freeze_rotation:
                R_desired = self.selected_body_init_offset.rotation().matrix()
            else:
                # Figure out the relative rotation of the hydra from its initial posture
                to_init_hydra_tf = self.grab_update_hydra_pose.inverse()
                desired_delta_rotation = to_init_hydra_tf.multiply(
                    self.desired_pose_in_world_frame).matrix()[:3, :3]
                # Transform the current object rotation into the init hydra frame, apply that relative tf, and
                # then transform back
                to_init_hydra_tf_rot = to_init_hydra_tf.matrix()[:3, :3]
                R_desired = to_init_hydra_tf_rot.T.dot(
                    desired_delta_rotation.dot(
                        to_init_hydra_tf_rot.dot(
                            self.selected_body_init_offset.rotation().matrix())
                    ))

            # Could also pull the rotation back, but it's kind of nice to be able to recenter the object
            # without messing up a randomized rotation.
            #R_desired = (self.desired_pose_in_world_frame.rotation().matrix()*self.attract_factor +
            #             R_desired*(1.-self.attract_factor))

            # Apply PD in cartesian space
            xyz_e = xyz_desired - xyz
            xyzd_e = -xyzd
            f = 100. * xyz_e + 10. * xyzd_e

            R_err_in_body_frame = np.linalg.inv(R).dot(R_desired)
            aa = AngleAxis(R_err_in_body_frame)
            tau_p = R.dot(aa.axis() * aa.angle())
            tau_d = -Rd
            tau = tau_p + 0.1 * tau_d

            exerted_force = SpatialForce(tau=tau, f=f)

            out = ExternallyAppliedSpatialForce()
            out.F_Bq_W = exerted_force
            out.body_index = self.selected_body.index()
            y_data.set_value(VectorExternallyAppliedSpatialForced([out]))
        else:
            y_data.set_value(VectorExternallyAppliedSpatialForced([]))
        self.callback_lock.release()