如何在Python中使用 Plot 画出一个简单的模型
在下面的程序中，首先要知道机器人的DH参数，然后计算出每一个关节的位置，最后利用 plot 函数画出关节之间的连杆就可以了，最后利用 animation 库来实现一个动画效果。
python
import matplotlib.pyplot as plt
import numpy as np
import matplotlib.pyplot as plt
import numpy as np
from IPython import embed
import matplotlib.animation as animation
from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg
import tkinter as tk
# 取消科学计数法，保留6位小数
np.set_printoptions(precision=6, suppress=True)
class Robot(object):
def __init__(self):
self.alpha_list = []
self.a_list = []
self.d_list = []
self.theta_list = []
def SetDHParamList(self, alpha_list, a_list, d_list, theta_list):
self.alpha_list = alpha_list
self.a_list = a_list
self.d_list = d_list
self.theta_list = theta_list
def DH(self, index, theta):
theta = theta + self.theta_list[index]
T = np.zeros([4, 4])
c_t = np.cos(theta * np.pi/180)
s_t = np.sin(theta * np.pi/180)
c_a = np.cos(self.alpha_list[index] * np.pi/180)
s_a = np.sin(self.alpha_list[index] * np.pi/180)
T[0] = [c_t, - s_t * c_a, s_t * s_a, self.a_list[index] * c_t]
T[1] = [s_t, c_t * c_a, - c_t * s_a, self.a_list[index] * s_t]
T[2] = [ 0, s_a, c_a, self.d_list[index]]
T[3] = [ 0, 0, 0, 1]
# print(T)
return np.mat(T)
def GetRobotTool(self, q_list):
T6 = np.identity(4, dtype= float)
for i in range(6):
T = self.DH(i, q_list[i])
T6 = T6 * T
return T6
class ShowRobot(object):
def __init__(self):
self.ax = None
self.robot = None
self.q_list = [0, 0, 0, 0, 0, 0]
fig_width, fig_height = plt.gcf().get_size_inches()
# 根据画布大小自动调整直线的粗细, 这里乘上系数3只是为了更好地显示效果
self.line_thicknes = max(fig_width / 50, fig_height / 50) * 60
self.s200 = max(fig_width / 50, fig_height / 50) * 200
self.fontsize = max(fig_width / 50, fig_height / 50) * 80
self.alpha = 0.7 #透明度
def ShowFrame(self, T, length = 1, width = 2):
# 使用quiver绘制坐标轴
# 参数说明：
# origin[0], origin[1], origin[2] 是箭头的起点
# x_axis[0], x_axis[1], x_axis[2] 是箭头的方向
# length 是箭头的长度
# arrow_length_ratio 是箭头头部与箭杆的比例
# linewidth 是箭杆的宽度
self.ax.quiver(T[0, 3], T[1, 3], T[2, 3], T[0, 0], T[1, 0], T[2, 0], color='r', length=length, arrow_length_ratio=0.1, linewidth=width)
self.ax.quiver(T[0, 3], T[1, 3], T[2, 3], T[0, 1], T[1, 1], T[2, 1], color='g', length=length, arrow_length_ratio=0.1, linewidth=width)
self.ax.quiver(T[0, 3], T[1, 3], T[2, 3], T[0, 2], T[1, 2], T[2, 2], color='b', length=length, arrow_length_ratio=0.1, linewidth=width)
def ShowLink(self, joint_index, T_start, T_end):
mx2, my2, mz2 = np.array([T_start[0, 3],T_end[0, 3]]), np.array([T_start[1, 3], T_end[1, 3]]), np.array([T_start[2, 3], T_end[2, 3]])
self.ax.plot(mx2, my2, mz2, solid_capstyle='round', color='blue', linewidth=self.line_thicknes, alpha=self.alpha)
self.ax.text(T_start[0, 3], T_start[1, 3], T_start[2, 3], "J" + str(joint_index), color='r', fontsize=self.fontsize, zorder=1, ha='center')
self.ax.scatter(T_start[0, 3], T_start[1, 3], T_start[2, 3], c='orange', marker='.', s=self.s200)
# 更新函数，用于每一帧的更新
def update(self, frame):
self.ax.cla() # 清除所有轴
# 设置坐标轴标签
self.ax.set_xlabel('X')
self.ax.set_ylabel('Y')
self.ax.set_zlabel('Z')
# # 设置图形显示范围
self.ax.set_xlim([-1000, 1000])
self.ax.set_ylim([-1000, 1000])
self.ax.set_zlim([-1000, 1000])
T_start = np.identity(4, dtype= float)
T_end = np.identity(4, dtype= float)
self.ShowFrame(T_start, length=300)
# 关节角度固定不变
self.q_list = [0, 0, 0, 0, 0, 0]
# 关节角度每一帧都在更新，呈现出一种动画效果
# self.q_list = [frame, frame - 90, 0, 0, 0, 0]
for joint_index in range(6):
T_start = T_end
T = self.robot.DH(joint_index, self.q_list[joint_index])
T_end = T_end * T
# print(T_end)
self.ShowLink(joint_index, T_start, T_end)
self.ShowFrame(T_end, length=300)
def APP():
L1 = 388
L2 = 50
L3 = 330
L4 = 50
L5 = 332
L6 = 96
alpha_list = [90, 0, 90, -90, 90, 0]
a_list = [L2, L3, L4, 0, 0, 0]
d_list = [L1, 0, 0, L5, 0, L6]
theta_list = [0, 90, 0, 0, 0, 0]
robot = Robot()
show_robot = ShowRobot()
robot.SetDHParamList(alpha_list, a_list, d_list, theta_list)
# 创建一个3D图形
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
show_robot.ax = ax
show_robot.robot = robot
root = tk.Tk()
canvas = FigureCanvasTkAgg(fig, master = root)
canvas.get_tk_widget().pack()
ani = animation.FuncAnimation(fig, show_robot.update, interval = 50)
canvas.draw()
tk.mainloop()
# 显示动画
plt.show()
if __name__ == "__main__":
APP()下面是实际显示出来的3D机器人模型，其中也画出了机器人的基坐标系和末端工具坐标系。
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在 Update 函数中，可以在每一帧中去更新关节角度，然后呈现出一种动画的效果。
python
# 关节角度固定不变
self.q_list = [0, 0, 0, 0, 0, 0]
# 关节角度每一帧都在更新，呈现出一种动画效果
# self.q_list = [frame, frame - 90, 0, 0, 0, 0]