下个星期就要参加中国工程机加粗样式器人大赛了,此之前一直是玩 类人形机器人以及ROS二轮差速小车,和三轮全向小车,从未涉及到四轴飞行器系列,因此,等我比完赛我要开始涉足四旋翼系列…
在淘宝上买了一些硬件之后,先不急,由于抱着练手 matplotlib 的心情来Python仿真四旋翼的飞行过程,在此之间趁机学习四旋翼飞行原理,所需的数学知识…
由于刚刚接触四旋翼,在仿真与实操的情况下,有可能哪里说得不对,那么,看过的小伙伴如果发现了我的错误,请留言告诉我,大家一起讨论…
首先,在桌面新建一个文件夹,名字自拟,反正我的叫做: Quadrotor…
然后我们就可以在此目录下,新建python脚本了…
我使用的编辑器是 Anaconda自带的 Spyder, 同时也用 Pycharm 和 Python自带的ide
打开 Spyder 我们新建 Python脚本,命名为:
Quadrotor.py
然后,就开始编写程序:
既然是 matplotlib 仿真,我们必然是要导入 特定的模块:
import matplotlib.pyplot as plt
导入这个模块我们是为了以图形的方式来展现我们的四旋翼飞机;
创建自定义3D图像;
plt.ion()
fig = plt.figure()
self.ax = fig.add_subplot(111, projection='3d')
plt.ion():
使用plt.ion()这个函数,使matplotlib的显示模式转换为交互(interactive)模式。即使在脚本中遇到plt.show(),代码还是会继续执行。有时候,在plt.show()之前一定不要忘了加plt.ioff(),如果不加,界面会一闪而过,并不会停留。那么动态图像是如何画出来的,请看下面这段代码:
在这里 介绍旋转矩阵:
维基百科解释的旋转矩阵
还有这篇:非常好!
http://blog.miskcoo.com/2016/12/rotation-in-3d-space
这是我建立的旋转矩阵函数:
在此之前,我们先导入标准库:
from math import cos, sin
还有特殊向量格式的numpy
import numpy as np
def transformation_matrix(self):
x = self.x
y = self.y
z = self.z
roll = self.roll
pitch = self.pitch
yaw = self.yaw
return np.array(
[[cos(yaw) * cos(pitch), -sin(yaw) * cos(roll) + cos(yaw) * sin(pitch) * sin(roll), sin(yaw) * sin(roll) + cos(yaw) * sin(pitch) * cos(roll), x],
[sin(yaw) * cos(pitch), cos(yaw) * cos(roll) + sin(yaw) * sin(pitch) *
sin(roll), -cos(yaw) * sin(roll) + sin(yaw) * sin(pitch) * cos(roll), y],
[-sin(pitch), cos(pitch) * sin(roll), cos(pitch) * cos(yaw), z]
])
此后,接着写:在这里面…
在这里我们必须注意了解的是这些函数:
1.np.matmul() 两个数组的矩阵乘积。
https://docs.scipy.org/doc/numpy-1.13.0/reference/generated/numpy.matmul.html2.plt.xlim 获取或设置当前x轴的限制。
https://matplotlib.org/api/_as_gen/matplotlib.pyplot.xlim.html
3.plt.ylim 获取或设置当前y轴的限制。
https://matplotlib.org/api/_as_gen/matplotlib.pyplot.xlim.html
4.plt.pause(0.001) 暂停间隔秒
https://matplotlib.org/api/_as_gen/matplotlib.pyplot.pause.html
5.np.array 创建一个数组
https://docs.scipy.org/doc/numpy/reference/generated/numpy.array.html
6.plt.cla() 清除当前轴
https://matplotlib.org/api/_as_gen/matplotlib.pyplot.cla.html
7.self.ax.plot 绘制y与x作为线和/或标记,也就是绘制图像
https://matplotlib.org/api/_as_gen/matplotlib.axes.Axes.plot.html
8.self.ax.set_zlim(0, 10) 设置z轴视图限制。
https://matplotlib.org/api/_as_gen/matplotlib.axes.Axes.set_xlim.html
def plot(self):
T = self.transformation_matrix()
p1_t = np.matmul(T, self.p1)
p2_t = np.matmul(T, self.p2)
p3_t = np.matmul(T, self.p3)
p4_t = np.matmul(T, self.p4)
plt.cla()
self.ax.plot([p1_t[0], p2_t[0], p3_t[0], p4_t[0]],
[p1_t[1], p2_t[1], p3_t[1], p4_t[1]],
[p1_t[2], p2_t[2], p3_t[2], p4_t[2]], 'k.')
self.ax.plot([p1_t[0], p2_t[0]], [p1_t[1], p2_t[1]],
[p1_t[2], p2_t[2]], 'r-')
self.ax.plot([p3_t[0], p4_t[0]], [p3_t[1], p4_t[1]],
[p3_t[2], p4_t[2]], 'r-')
self.ax.plot(self.x_data, self.y_data, self.z_data, 'b:')
plt.xlim(-5, 5)
plt.ylim(-5, 5)
self.ax.set_zlim(0, 10)
plt.pause(0.001)
然后,补充剩下的初始代码:
class Quadrotor():
def __init__(self, x=0, y=0, z=0, roll=0, pitch=0, yaw=0, size=1, show_animation=True):
self.p1 = np.array([size / 2, 0, 0, 1]).T
self.p2 = np.array([-size / 2, 0, 0, 1]).T
self.p3 = np.array([0, size / 2, 0, 1]).T
self.p4 = np.array([0, -size / 2, 0, 1]).T
self.x_data = []
self.y_data = []
self.z_data = []
self.show_animation = show_animation
if self.show_animation:
plt.ion()
fig = plt.figure()
self.ax = fig.add_subplot(111, projection='3d')
self.update_pose(x, y, z, roll, pitch, yaw)
def update_pose(self, x, y, z, roll, pitch, yaw):
self.x = x
self.y = y
self.z = z
self.roll = roll
self.pitch = pitch
self.yaw = yaw
self.x_data.append(x)
self.y_data.append(y)
self.z_data.append(z)
if self.show_animation:
self.plot()
完整代码如下:
from math import cos, sin
import numpy as np
import matplotlib.pyplot as plt
#size=0.25
class Quadrotor():
def __init__(self, x=0, y=0, z=0, roll=0, pitch=0, yaw=0, size=1, show_animation=True):
self.p1 = np.array([size / 2, 0, 0, 1]).T
self.p2 = np.array([-size / 2, 0, 0, 1]).T
self.p3 = np.array([0, size / 2, 0, 1]).T
self.p4 = np.array([0, -size / 2, 0, 1]).T
self.x_data = []
self.y_data = []
self.z_data = []
self.show_animation = show_animation
if self.show_animation:
plt.ion()
fig = plt.figure()
self.ax = fig.add_subplot(111, projection='3d')
self.update_pose(x, y, z, roll, pitch, yaw)
def update_pose(self, x, y, z, roll, pitch, yaw):
self.x = x
self.y = y
self.z = z
self.roll = roll
self.pitch = pitch
self.yaw = yaw
self.x_data.append(x)
self.y_data.append(y)
self.z_data.append(z)
if self.show_animation:
self.plot()
def transformation_matrix(self):
x = self.x
y = self.y
z = self.z
roll = self.roll
pitch = self.pitch
yaw = self.yaw
return np.array(
[[cos(yaw) * cos(pitch), -sin(yaw) * cos(roll) + cos(yaw) * sin(pitch) * sin(roll), sin(yaw) * sin(roll) + cos(yaw) * sin(pitch) * cos(roll), x],
[sin(yaw) * cos(pitch), cos(yaw) * cos(roll) + sin(yaw) * sin(pitch) *
sin(roll), -cos(yaw) * sin(roll) + sin(yaw) * sin(pitch) * cos(roll), y],
[-sin(pitch), cos(pitch) * sin(roll), cos(pitch) * cos(yaw), z]
])
def plot(self):
T = self.transformation_matrix()
p1_t = np.matmul(T, self.p1)
p2_t = np.matmul(T, self.p2)
p3_t = np.matmul(T, self.p3)
p4_t = np.matmul(T, self.p4)
plt.cla()
self.ax.plot([p1_t[0], p2_t[0], p3_t[0], p4_t[0]],
[p1_t[1], p2_t[1], p3_t[1], p4_t[1]],
[p1_t[2], p2_t[2], p3_t[2], p4_t[2]], 'k.')
self.ax.plot([p1_t[0], p2_t[0]], [p1_t[1], p2_t[1]],
[p1_t[2], p2_t[2]], 'r-')
self.ax.plot([p3_t[0], p4_t[0]], [p3_t[1], p4_t[1]],
[p3_t[2], p4_t[2]], 'r-')
self.ax.plot(self.x_data, self.y_data, self.z_data, 'b:')
plt.xlim(-5, 5)
plt.ylim(-5, 5)
self.ax.set_zlim(0, 10)
plt.pause(0.001)
q = Quadrotor(x=-5, y=5, z=5, roll=0,pitch=0, yaw=0, size=1, show_animation=True)
#q.plot()
看过的小伙伴如果发现了我的错误,请留言告诉我哦!,大家一起讨论…