forked from logzhan/ORB-SLAM3-UESTC
225 lines
7.4 KiB
Python
225 lines
7.4 KiB
Python
import sympy
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import sys
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import unittest
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import sophus
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import functools
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class Se2:
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""" 2 dimensional group of rigid body transformations """
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def __init__(self, so2, t):
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""" internally represented by a unit complex number z and a translation
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2-vector """
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self.so2 = so2
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self.t = t
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@staticmethod
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def exp(v):
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""" exponential map """
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theta = v[2]
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so2 = sophus.So2.exp(theta)
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a = so2.z.imag / theta
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b = (1 - so2.z.real) / theta
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t = sophus.Vector2(a * v[0] - b * v[1],
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b * v[0] + a * v[1])
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return Se2(so2, t)
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def log(self):
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theta = self.so2.log()
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halftheta = 0.5 * theta
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a = -(halftheta * self.so2.z.imag) / (self.so2.z.real - 1)
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V_inv = sympy.Matrix([[a, halftheta],
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[-halftheta, a]])
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upsilon = V_inv * self.t
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return sophus.Vector3(upsilon[0], upsilon[1], theta)
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def __repr__(self):
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return "Se2: [" + repr(self.so2) + " " + repr(self.t)
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@staticmethod
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def hat(v):
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upsilon = sophus.Vector2(v[0], v[1])
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theta = v[2]
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return sophus.So2.hat(theta).\
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row_join(upsilon).\
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col_join(sympy.Matrix.zeros(1, 3))
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def matrix(self):
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""" returns matrix representation """
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R = self.so2.matrix()
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return (R.row_join(self.t)).col_join(sympy.Matrix(1, 3, [0, 0, 1]))
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def __mul__(self, right):
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""" left-multiplication
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either rotation concatenation or point-transform """
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if isinstance(right, sympy.Matrix):
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assert right.shape == (2, 1), right.shape
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return self.so2 * right + self.t
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elif isinstance(right, Se2):
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return Se2(self.so2 * right.so2,
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self.t + self.so2 * right.t)
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assert False, "unsupported type: {0}".format(type(right))
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def __getitem__(self, key):
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""" We use the following convention [q0, q1, q2, q3, t0, t1, t2] """
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assert (key >= 0 and key < 4)
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if key < 2:
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return self.so2[key]
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else:
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return self.t[key - 2]
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@staticmethod
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def calc_Dx_exp_x(x):
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return sympy.Matrix(4, 3, lambda r, c:
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sympy.diff(Se2.exp(x)[r], x[c]))
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@staticmethod
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def Dx_exp_x_at_0():
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return sympy.Matrix([[0, 0, 0],
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[0, 0, 1],
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[1, 0, 0],
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[0, 1, 0]])
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def calc_Dx_this_mul_exp_x_at_0(self, x):
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v = Se2.exp(x)
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return sympy.Matrix(4, 3, lambda r, c:
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sympy.diff((self * Se2.exp(x))[r], x[c])). \
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subs(x[0], 0).subs(x[1], 0).limit(x[2], 0)
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@staticmethod
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def calc_Dx_exp_x_at_0(x):
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return Se2.calc_Dx_exp_x(x).subs(x[0], 0).subs(x[1], 0).limit(x[2], 0)
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@staticmethod
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def Dxi_x_matrix(x, i):
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if i < 2:
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return sophus.So2.Dxi_x_matrix(x, i).\
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row_join(sympy.Matrix.zeros(2, 1)).\
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col_join(sympy.Matrix.zeros(1, 3))
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M = sympy.Matrix.zeros(3, 3)
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M[i - 2, 2] = 1
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return M
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@staticmethod
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def calc_Dxi_x_matrix(x, i):
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return sympy.Matrix(3, 3, lambda r, c:
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sympy.diff(x.matrix()[r, c], x[i]))
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@staticmethod
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def Dxi_exp_x_matrix(x, i):
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T = Se2.exp(x)
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Dx_exp_x = Se2.calc_Dx_exp_x(x)
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l = [Dx_exp_x[j, i] * Se2.Dxi_x_matrix(T, j) for j in range(0, 4)]
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return functools.reduce((lambda a, b: a + b), l)
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@staticmethod
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def calc_Dxi_exp_x_matrix(x, i):
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return sympy.Matrix(3, 3, lambda r, c:
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sympy.diff(Se2.exp(x).matrix()[r, c], x[i]))
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@staticmethod
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def Dxi_exp_x_matrix_at_0(i):
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v = sophus.ZeroVector3()
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v[i] = 1
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return Se2.hat(v)
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@staticmethod
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def calc_Dxi_exp_x_matrix_at_0(x, i):
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return sympy.Matrix(3, 3, lambda r, c:
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sympy.diff(Se2.exp(x).matrix()[r, c], x[i])
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).subs(x[0], 0).subs(x[1], 0).limit(x[2], 0)
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class TestSe2(unittest.TestCase):
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def setUp(self):
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upsilon0, upsilon1, theta = sympy.symbols(
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'upsilon[0], upsilon[1], theta',
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real=True)
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x, y = sympy.symbols('c[0] c[1]', real=True)
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p0, p1 = sympy.symbols('p0 p1', real=True)
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t0, t1 = sympy.symbols('t[0] t[1]', real=True)
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self.upsilon_theta = sophus.Vector3(
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upsilon0, upsilon1, theta)
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self.t = sophus.Vector2(t0, t1)
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self.a = Se2(sophus.So2(sophus.Complex(x, y)), self.t)
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self.p = sophus.Vector2(p0, p1)
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def test_exp_log(self):
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for v in [sophus.Vector3(0., 1, 0.5),
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sophus.Vector3(0.1, 0.1, 0.1),
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sophus.Vector3(0.01, 0.2, 0.03)]:
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w = Se2.exp(v).log()
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for i in range(0, 3):
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self.assertAlmostEqual(v[i], w[i])
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def test_matrix(self):
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T_foo_bar = Se2.exp(self.upsilon_theta)
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Tmat_foo_bar = T_foo_bar.matrix()
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point_bar = self.p
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p1_foo = T_foo_bar * point_bar
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p2_foo = sophus.proj(Tmat_foo_bar * sophus.unproj(point_bar))
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self.assertEqual(sympy.simplify(p1_foo - p2_foo),
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sophus.ZeroVector2())
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def test_derivatives(self):
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self.assertEqual(sympy.simplify(
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Se2.calc_Dx_exp_x_at_0(self.upsilon_theta) -
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Se2.Dx_exp_x_at_0()),
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sympy.Matrix.zeros(4, 3))
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for i in range(0, 4):
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self.assertEqual(sympy.simplify(Se2.calc_Dxi_x_matrix(self.a, i) -
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Se2.Dxi_x_matrix(self.a, i)),
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sympy.Matrix.zeros(3, 3))
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for i in range(0, 3):
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self.assertEqual(sympy.simplify(
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Se2.Dxi_exp_x_matrix(self.upsilon_theta, i) -
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Se2.calc_Dxi_exp_x_matrix(self.upsilon_theta, i)),
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sympy.Matrix.zeros(3, 3))
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self.assertEqual(sympy.simplify(
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Se2.Dxi_exp_x_matrix_at_0(i) -
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Se2.calc_Dxi_exp_x_matrix_at_0(self.upsilon_theta, i)),
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sympy.Matrix.zeros(3, 3))
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def test_codegen(self):
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stream = sophus.cse_codegen(Se2.calc_Dx_exp_x(self.upsilon_theta))
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filename = "cpp_gencode/Se2_Dx_exp_x.cpp"
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# set to true to generate codegen files
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if False:
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file = open(filename, "w")
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for line in stream:
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file.write(line)
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file.close()
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else:
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file = open(filename, "r")
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file_lines = file.readlines()
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for i, line in enumerate(stream):
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self.assertEqual(line, file_lines[i])
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file.close()
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stream.close
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stream = sophus.cse_codegen(self.a.calc_Dx_this_mul_exp_x_at_0(
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self.upsilon_theta))
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filename = "cpp_gencode/Se2_Dx_this_mul_exp_x_at_0.cpp"
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# set to true to generate codegen files
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if False:
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file = open(filename, "w")
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for line in stream:
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file.write(line)
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file.close()
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else:
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file = open(filename, "r")
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file_lines = file.readlines()
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for i, line in enumerate(stream):
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self.assertEqual(line, file_lines[i])
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file.close()
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stream.close
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if __name__ == '__main__':
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unittest.main()
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