Files
PythonRobotics/ArmNavigation/n_joint_arm_3d/NLinkArm.py
2019-01-26 02:23:53 +09:00

212 lines
7.5 KiB
Python

import numpy as np
import math
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
class Link:
def __init__(self, dh_params):
self.dh_params_ = dh_params
def transformation_matrix(self):
theta = self.dh_params_[0]
alpha = self.dh_params_[1]
a = self.dh_params_[2]
d = self.dh_params_[3]
'''
trans = np.array(
[[math.cos(theta), -math.sin(theta), 0, a],
[math.cos(alpha) * math.sin(theta), math.cos(alpha) * math.cos(theta), -math.sin(alpha), -d * math.sin(alpha)],
[math.sin(alpha) * math.sin(theta), math.sin(alpha) * math.cos(theta), math.cos(alpha), d * math.cos(alpha)],
[0, 0, 0, 1]])
'''
st = math.sin(theta)
ct = math.cos(theta)
sa = math.sin(alpha)
ca = math.cos(alpha)
trans = np.array([[ct, -st * ca, st * sa, a * ct],
[st, ct * ca, -ct * sa, a * st],
[0, sa, ca, d],
[0, 0, 0, 1]])
return trans
def basic_jacobian(self, trans_prev, ee_pose):
pos_prev = np.array([trans_prev[0, 3], trans_prev[1, 3], trans_prev[2, 3]])
z_axis_prev = np.array([trans_prev[0, 2], trans_prev[1, 2], trans_prev[2, 2]])
basic_jacobian = np.hstack((np.cross(z_axis_prev, ee_pose - pos_prev), z_axis_prev))
return basic_jacobian
class NLinkArm:
def __init__(self, dh_params_list):
self.link_list = []
for i in range(len(dh_params_list)):
self.link_list.append(Link(dh_params_list[i]))
def transformation_matrix(self):
trans = np.identity(4)
for i in range(len(self.link_list)):
trans = np.dot(trans, self.link_list[i].transformation_matrix())
return trans
def forward_kinematics(self, plot=False):
trans = self.transformation_matrix()
x = trans[0, 3]
y = trans[1, 3]
z = trans[2, 3]
alpha, beta, gamma = self.calc_euler_angle()
if plot:
self.fig = plt.figure()
self.ax = Axes3D(self.fig)
x_list = []
y_list = []
z_list = []
trans = np.identity(4)
x_list.append(trans[0, 3])
y_list.append(trans[1, 3])
z_list.append(trans[2, 3])
for i in range(len(self.link_list)):
trans = np.dot(trans, self.link_list[i].transformation_matrix())
x_list.append(trans[0, 3])
y_list.append(trans[1, 3])
z_list.append(trans[2, 3])
self.ax.plot(x_list, y_list, z_list, "o-", color="#00aa00", ms=4, mew=0.5)
self.ax.plot([0], [0], [0], "o")
self.ax.set_xlim(-1, 1)
self.ax.set_ylim(-1, 1)
self.ax.set_zlim(-1, 1)
plt.show()
return [x, y, z, alpha, beta, gamma]
def basic_jacobian(self, ee_pose):
basic_jacobian_mat = []
trans = np.identity(4)
for i in range(len(self.link_list)):
basic_jacobian_mat.append(self.link_list[i].basic_jacobian(trans, ee_pose[0:3]))
trans = np.dot(trans, self.link_list[i].transformation_matrix())
return np.array(basic_jacobian_mat).T
def inverse_kinematics(self, ref_ee_pose, plot=False):
for cnt in range(500):
ee_pose = self.forward_kinematics()
diff_pose = np.array(ref_ee_pose) - ee_pose
basic_jacobian_mat = self.basic_jacobian(ee_pose)
alpha, beta, gamma = self.calc_euler_angle()
K_zyz = np.array([[0, -math.sin(alpha), math.cos(alpha) * math.sin(beta)],
[0, math.cos(alpha), math.sin(alpha) * math.sin(beta)],
[1, 0, math.cos(beta)]])
K_alpha = np.identity(6)
K_alpha[3:, 3:] = K_zyz
theta_dot = np.dot(np.dot(np.linalg.pinv(basic_jacobian_mat), K_alpha), np.array(diff_pose))
self.update_joint_angles(theta_dot / 100.)
if plot:
self.fig = plt.figure()
self.ax = Axes3D(self.fig)
x_list = []
y_list = []
z_list = []
trans = np.identity(4)
x_list.append(trans[0, 3])
y_list.append(trans[1, 3])
z_list.append(trans[2, 3])
for i in range(len(self.link_list)):
trans = np.dot(trans, self.link_list[i].transformation_matrix())
x_list.append(trans[0, 3])
y_list.append(trans[1, 3])
z_list.append(trans[2, 3])
self.ax.plot(x_list, y_list, z_list, "o-", color="#00aa00", ms=4, mew=0.5)
self.ax.plot([0], [0], [0], "o")
self.ax.set_xlim(-1, 1)
self.ax.set_ylim(-1, 1)
self.ax.set_zlim(-1, 1)
self.ax.plot([ref_ee_pose[0]], [ref_ee_pose[1]], [ref_ee_pose[2]], "o")
plt.show()
def calc_euler_angle(self):
trans = self.transformation_matrix()
alpha = math.atan2(trans[1][2], trans[0][2])
if -math.pi / 2 <= alpha and alpha <= math.pi / 2:
alpha = math.atan2(trans[1][2], trans[0][2]) + math.pi
if -math.pi / 2 <= alpha and alpha <= math.pi / 2:
alpha = math.atan2(trans[1][2], trans[0][2]) - math.pi
beta = math.atan2(trans[0][2] * math.cos(alpha) + trans[1][2] * math.sin(alpha), trans[2][2])
gamma = math.atan2(-trans[0][0] * math.sin(alpha) + trans[1][0] * math.cos(alpha), -trans[0][1] * math.sin(alpha) + trans[1][1] * math.cos(alpha))
return alpha, beta, gamma
def set_joint_angles(self, joint_angle_list):
for i in range(len(self.link_list)):
self.link_list[i].dh_params_[0] = joint_angle_list[i]
def update_joint_angles(self, diff_joint_angle_list):
for i in range(len(self.link_list)):
self.link_list[i].dh_params_[0] += diff_joint_angle_list[i]
def plot(self):
self.fig = plt.figure()
self.ax = Axes3D(self.fig)
x_list = []
y_list = []
z_list = []
trans = np.identity(4)
x_list.append(trans[0, 3])
y_list.append(trans[1, 3])
z_list.append(trans[2, 3])
for i in range(len(self.link_list)):
trans = np.dot(trans, self.link_list[i].transformation_matrix())
x_list.append(trans[0, 3])
y_list.append(trans[1, 3])
z_list.append(trans[2, 3])
self.ax.plot(x_list, y_list, z_list, "o-", color="#00aa00", ms=4, mew=0.5)
self.ax.plot([0], [0], [0], "o")
self.ax.set_xlabel("x")
self.ax.set_ylabel("y")
self.ax.set_zlabel("z")
self.ax.set_xlim(-1, 1)
self.ax.set_ylim(-1, 1)
self.ax.set_zlim(-1, 1)
plt.show()
if __name__ == "__main__":
n_link_arm = NLinkArm([[0., -math.pi/2, .1, 0.],
[math.pi/2, math.pi/2, 0., 0.],
[0., -math.pi/2, 0., .4],
[0., math.pi/2, 0., 0.],
[0., -math.pi/2, 0., .321],
[0., math.pi/2, 0., 0.],
[0., 0., 0., 0.]])
print(n_link_arm.forward_kinematics())
n_link_arm.set_joint_angles([1, 1, 1, 1, 1, 1, 1])
n_link_arm.plot()