python的numpy教程_ROS与Python入门教程使用numpy

ROS与Python入门教程-使用numpy

说明

这一节介绍numpy&＃xff0c;它是针对科学计算的python软件包, 用于处理传感器数据&＃xff0c;数组数据等。

在本教程中&＃xff0c;我们将使用rospy.numpy_msg模块。这个模块带有numpy_msg()的封装&＃xff0c;它允许节点在适当的地方反序列化消息直接进入NumPy数组。numpy_msg()封装也可以用来发布包含NumPy数组数据信息。

创建包numpy_tutorial

创建新包&＃xff0c;依赖numpy_tutorial&＃xff0c;依赖rospy_tutorials的消息类型。

catkin_create_pkg numpy_tutorial rospy rospy_tutorials

查看rospy_tutorials的消息类型

$ rosmsg show rospy_tutorials/Floats

float32[] data

需要依赖python-numpy,添加下面两行代码到在package.xml文件里。

python-numpy

python-numpy

创建没使用numpy的listener节点

创建节点_listener.py, 用来订阅floats主题。

$ cd ~/catkin_ws/src/numpy_tutorial

$ mkdir scripts

$ cd scripts

$ touch numpy_listener.py

$ chmod &＃43;x numpy_listener.py

$ vim numpy_listener.py

手工输入代码&＃xff1a;

#!/usr/bin/env python

import rospy

from rospy_tutorials.msg import Floats

def callback(data):

print rospy.get_name(), "I heard %s"%str(data.data)

def listener():

rospy.init_node(&＃39;listener&＃39;)

rospy.Subscriber("floats", Floats, callback)

rospy.spin()

if __name__ &＃61;&＃61; &＃39;__main__&＃39;:

listener()

测试listener节点

新开终端&＃xff0c;启动roscore

$ roscore

新开终端&＃xff0c;启动订阅节点

$ rosrun numpy_tutorial numpy_listener.py

新开终端&＃xff0c;发布主题

$ rostopic pub -r 1 floats rospy_tutorials/Floats "[1.1, 2.2, 3.3, 4.4, 5.5]"

效果&＃xff1a;

$ rosrun numpy_tutorial numpy_listener.py

/listener-977-1248226102144 I heard (1.1000000238418579, 2.2000000476837158, 3.2999999523162842, 4.4000000953674316, 5.5)

/listener-977-1248226102144 I heard (1.1000000238418579, 2.2000000476837158, 3.2999999523162842, 4.4000000953674316, 5.5)

... and so on

使用Numpy的listener节点

更改节点&＃xff0c;需要变化: 导入numpy_msg&＃xff0c; 在订阅指定numpy_msg函数处理的浮点值。

from rospy.numpy_msg import numpy_msg

...

rospy.Subscriber("floats", numpy_msg(Floats), callback)

更改代码为&＃xff1a;

#!/usr/bin/env python

import rospy

from rospy_tutorials.msg import Floats

from rospy.numpy_msg import numpy_msg

def callback(data):

print rospy.get_name(), "I heard %s"%str(data.data)

def listener():

rospy.init_node(&＃39;listener&＃39;)

rospy.Subscriber("floats", numpy_msg(Floats), callback)

rospy.spin()

if __name__ &＃61;&＃61; &＃39;__main__&＃39;:

listener()

测试使用Numpy的listener节点

新开终端&＃xff0c;启动roscore

$ roscore

新开终端&＃xff0c;启动订阅节点

$ rosrun numpy_tutorial numpy_listener.py

发布主题

$ rostopic pub -r 1 floats rospy_tutorials/Floats "[1.1, 2.2, 3.3, 4.4, 5.5]"

效果&＃xff1a;&＃xff08;跟之前稍有不同&＃xff0c;就是位数变化&＃xff0c;返回的是numpy数组格式&＃xff09;

$ rosrun rospy_tutorials listener_numpy.py

/listener-1243-1248226610835 I heard [ 1.10000002 2.20000005 3.29999995 4.4000001 5.5 ]

/listener-1243-1248226610835 I heard [ 1.10000002 2.20000005 3.29999995 4.4000001 5.5 ]

... and so on

使用Numpy的Talker节点

Talker节点需要正确处理Numpy的数组的数据格式

在scripts新建numpy_talker.py

$ cd ~/catkin_ws/src/numpy_tutorial

$ mkdir scripts

$ cd scripts

$ touch numpy_talker.py

$ chmod &＃43;x numpy_talker.py

$ vim numpy_talker.py

手工输入如下代码&＃xff1a;

#!/usr/bin/env python

import rospy

from rospy.numpy_msg import numpy_msg

from rospy_tutorials.msg import Floats

import numpy

def talker():

pub &＃61; rospy.Publisher(&＃39;floats&＃39;, numpy_msg(Floats),queue_size&＃61;10)

rospy.init_node(&＃39;talker&＃39;, anonymous&＃61;True)

r &＃61; rospy.Rate(10) # 10hz

while not rospy.is_shutdown():

a &＃61; numpy.array([1.0, 2.1, 3.2, 4.3, 5.4, 6.5], dtype&＃61;numpy.float32)

pub.publish(a)

r.sleep()

if __name__ &＃61;&＃61; &＃39;__main__&＃39;:

talker()

代码分析&＃xff1a;

代码&＃xff1a;pub &＃61; rospy.Publisher(&＃39;floats&＃39;, numpy_msg(Floats))

分析&＃xff1a;发布经过numpy_msg函数来处理浮点值内容

代码&＃xff1a;a &＃61; numpy.array([1.0, 2.1, 3.2, 4.3, 5.4, 6.5], dtype&＃61;numpy.float32)

分析&＃xff1a;利用numpy.array来转换成numpy的数组结构&＃xff0c;并要指定内容的数据格式&＃xff0c;这是float32

测试使用numpy的Talker节点

新开终端&＃xff0c;启动roscore

$ roscore

新开终端&＃xff0c;启动订阅节点

$ rosrun numpy_tutorial numpy_listener.py

新开终端&＃xff0c;启动发布节点

$ rosrun numpy_tutorial numpy_talker.py

效果&＃xff1a;

$ rosrun rospy_tutorials listener_numpy.py

/listener-1423-1248226794834 I heard [ 1. 2.0999999 3.20000005 4.30000019 5.4000001 6.5 ]

/listener-1423-1248226794834 I heard [ 1. 2.0999999 3.20000005 4.30000019 5.4000001 6.5 ]

... and so on