gtsam/python/gtsam/tests/test_Sim3.py

135 lines
4.5 KiB
Python

"""
GTSAM Copyright 2010-2019, Georgia Tech Research Corporation,
Atlanta, Georgia 30332-0415
All Rights Reserved
See LICENSE for the license information
Sim3 unit tests.
Author: John Lambert
"""
# pylint: disable=no-name-in-module
import unittest
import numpy as np
import gtsam
from gtsam import Point3, Pose3, Pose3Pairs, Rot3, Similarity3
from gtsam.utils.test_case import GtsamTestCase
class TestSim3(GtsamTestCase):
"""Test selected Sim3 methods."""
def test_align_poses_along_straight_line(self):
"""Test Align Pose3Pairs method.
Scenario:
3 object poses
same scale (no gauge ambiguity)
world frame has poses rotated about x-axis (90 degree roll)
world and egovehicle frame translated by 15 meters w.r.t. each other
"""
Rx90 = Rot3.Rx(np.deg2rad(90))
# Create source poses (three objects o1, o2, o3 living in the egovehicle "e" frame)
# Suppose they are 3d cuboids detected by an onboard sensor in the egovehicle frame
eTo0 = Pose3(Rot3(), np.array([5, 0, 0]))
eTo1 = Pose3(Rot3(), np.array([10, 0, 0]))
eTo2 = Pose3(Rot3(), np.array([15, 0, 0]))
eToi_list = [eTo0, eTo1, eTo2]
# Create destination poses
# (same three objects, but instead living in the world/city "w" frame)
wTo0 = Pose3(Rx90, np.array([-10, 0, 0]))
wTo1 = Pose3(Rx90, np.array([-5, 0, 0]))
wTo2 = Pose3(Rx90, np.array([0, 0, 0]))
wToi_list = [wTo0, wTo1, wTo2]
we_pairs = Pose3Pairs(list(zip(wToi_list, eToi_list)))
# Recover the transformation wSe (i.e. world_S_egovehicle)
wSe = Similarity3.Align(we_pairs)
for wToi, eToi in zip(wToi_list, eToi_list):
self.gtsamAssertEquals(wToi, wSe.transformFrom(eToi))
def test_align_poses_along_straight_line_gauge(self):
"""Test if Align Pose3Pairs method can account for gauge ambiguity.
Scenario:
3 object poses
with gauge ambiguity (2x scale)
world frame has poses rotated about z-axis (90 degree yaw)
world and egovehicle frame translated by 11 meters w.r.t. each other
"""
Rz90 = Rot3.Rz(np.deg2rad(90))
# Create source poses (three objects o1, o2, o3 living in the egovehicle "e" frame)
# Suppose they are 3d cuboids detected by an onboard sensor in the egovehicle frame
eTo0 = Pose3(Rot3(), np.array([1, 0, 0]))
eTo1 = Pose3(Rot3(), np.array([2, 0, 0]))
eTo2 = Pose3(Rot3(), np.array([4, 0, 0]))
eToi_list = [eTo0, eTo1, eTo2]
# Create destination poses
# (same three objects, but instead living in the world/city "w" frame)
wTo0 = Pose3(Rz90, np.array([0, 12, 0]))
wTo1 = Pose3(Rz90, np.array([0, 14, 0]))
wTo2 = Pose3(Rz90, np.array([0, 18, 0]))
wToi_list = [wTo0, wTo1, wTo2]
we_pairs = Pose3Pairs(list(zip(wToi_list, eToi_list)))
# Recover the transformation wSe (i.e. world_S_egovehicle)
wSe = Similarity3.Align(we_pairs)
for wToi, eToi in zip(wToi_list, eToi_list):
self.gtsamAssertEquals(wToi, wSe.transformFrom(eToi))
def test_align_poses_scaled_squares(self):
"""Test if Align Pose3Pairs method can account for gauge ambiguity.
Make sure a big and small square can be aligned.
The u's represent a big square (10x10), and v's represents a small square (4x4).
Scenario:
4 object poses
with gauge ambiguity (2.5x scale)
"""
# 0, 90, 180, and 270 degrees yaw
R0 = Rot3.Rz(np.deg2rad(0))
R90 = Rot3.Rz(np.deg2rad(90))
R180 = Rot3.Rz(np.deg2rad(180))
R270 = Rot3.Rz(np.deg2rad(270))
aTi0 = Pose3(R0, np.array([2, 3, 0]))
aTi1 = Pose3(R90, np.array([12, 3, 0]))
aTi2 = Pose3(R180, np.array([12, 13, 0]))
aTi3 = Pose3(R270, np.array([2, 13, 0]))
aTi_list = [aTi0, aTi1, aTi2, aTi3]
bTi0 = Pose3(R0, np.array([4, 3, 0]))
bTi1 = Pose3(R90, np.array([8, 3, 0]))
bTi2 = Pose3(R180, np.array([8, 7, 0]))
bTi3 = Pose3(R270, np.array([4, 7, 0]))
bTi_list = [bTi0, bTi1, bTi2, bTi3]
ab_pairs = Pose3Pairs(list(zip(aTi_list, bTi_list)))
# Recover the transformation wSe (i.e. world_S_egovehicle)
aSb = Similarity3.Align(ab_pairs)
for aTi, bTi in zip(aTi_list, bTi_list):
self.gtsamAssertEquals(aTi, aSb.transformFrom(bTi))
if __name__ == "__main__":
unittest.main()