Пример #1
0
    def disturb_pose(self, pose, noise):
        """ uniform disturb pose

      pose
      noise  float, deviation angle in radius
    """
        new_pose = pose.copy()

        noise3d = noise / np.sqrt(3)
        new_pose[:3] += uniform(-noise3d, noise3d, 3)

        for jstar, jdof in zip(self.pos_start, self.joint_dof):
            if jdof == 1:
                new_pose[jstar] += uniform(-noise, noise)
            elif jdof == 4:
                noise_quat = Quaternion.fromExpMap(
                    uniform(-noise3d, noise3d, 3))
                ori_quat = Quaternion.fromWXYZ(pose[jstar:jstar + 4])
                new_quat = noise_quat.mul(ori_quat)
                new_pose[jstar:jstar + 4] = new_quat.wxyz()
            elif jdof == 0:
                pass
            else:
                assert (False and "not support jdof other than 1 and 4")

        return new_pose
Пример #2
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    def exp_to_action(self, expmap):
        """ Convert action represented in exponential map to angle-axis action
        which deepmimic_sim can take in

      Inputs:
        expmap      np.array of float, action represented in exponential map

      Outputs:
        action      np.array of float, action for deepmimic environment
    """
        assert (expmap.size == self.expdof)
        action = np.zeros(self.dof - 7)

        for i in range(1, self.num_joints):
            dof = self.joint_dof[i]
            e_off = self.exp_start[i]
            a_off = self.act_start[i]
            if dof == 1:  # revolute
                action[a_off] = expmap[e_off]
            elif dof == 4:  # spherical
                quata = Quaternion.fromExpMap(expmap[e_off:e_off + 3])
                action[a_off:a_off + 4] = quata.angaxis()

        assert (np.isfinite(sum(action))), embed()  #(action, targ_pose)
        return action
Пример #3
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    def exp_to_targ_pose_old(self, expmap):
        """ Convert action represented in exponential map to angle-axis action
        which deepmimic_sim can take in

      Inputs:
        expmap      np.array of float, action represented in exponential map

      Outputs:
        pose        np.array of float, pose of character
    """
        assert (expmap.size == self.expdof)
        pose = np.zeros(self.dof)

        for i in range(1, self.num_joints):
            dof = self.joint_dof[i]
            e_off = self.exp_start[i]
            p_off = self.pos_start[i]
            if dof == 1:  # revolute
                pose[p_off] = expmap[e_off]
            elif dof == 4:  # spherical
                quata = Quaternion.fromExpMap(expmap[e_off:e_off + 3])
                pose[p_off:p_off + 4] = quata.wxyz()

        assert (np.isfinite(sum(pose))), embed()  #(action, targ_pose)
        return pose
Пример #4
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 def buildHeadingTrans(self, rot):
     """ Build the rotation that rotate to local coordinate
   rot     np.array of float, 4 dim, (w, x, y, z) quat of coordinate orientation
 """
     theta = self._kin_core.getHeadingTheta(rot)
     inv_rot = Quaternion.fromExpMap(np.array([0, -theta, 0]))
     return inv_rot
Пример #5
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    def disturb_root_pose(self, pose, pos_noise, ori_noise):
        """ uniform disturb pose root
    """
        new_pose = pose.copy()

        noise3d = pos_noise / np.sqrt(3)
        new_pose[:3] += uniform(-noise3d, noise3d, 3)

        noise3d = ori_noise / np.sqrt(3)
        noise_quat = Quaternion.fromExpMap(uniform(-noise3d, noise3d, 3))
        ori_quat = Quaternion.fromWXYZ(pose[3:7])
        new_quat = noise_quat.mul(ori_quat)
        new_pose[3:7] = new_quat.wxyz()

        return new_pose