机器人编程按时巡线_ros机器人编程实践（12.2）- 用turtlebot仿真巡线机器人
前言
巡线设计
用自定义的图片设计gazebo的地板
首先我们需要设计一个gazebo的地板，这里感谢前辈的回答：参考问答
第一步：在home目录下ctrl+h显示隐藏文件
第二步：在.gazebo文件夹创建如下文件夹
mkdir ~/.gazebo/models/my_ground_plane
mkdir -p ~/.gazebo/models/my_ground_plane/materials/textures
mkdir -p ~/.gazebo/models/my_ground_plane/materials/scripts
第三步：创建材料文件
cd ~/.gazebo/models/my_ground_plane/materials/scripts
vi my_ground_plane.material
my_ground_plane.material文件如下：
material MyGroundPlane/Image
{
receive_shadows on
technique
{
pass
{
ambient 0.5 0.5 0.5 1.0
texture_unit
{
texture MyImage.png
}
}
}
}
第四步：在textures下存我们想要用的地板图片MyImage.png
如图，将它放到~/.gazebo/models/my_ground_plane/materials/textures下面
可以使用命令：
cp 你的图片路径/MyImage.png ~/.gazebo/models/my_ground_plane/materials/textures/
第五步：在my_ground_plane文件夹下，创建文件model.sdf
cd ~/.gazebo/models/my_ground_plane
vi model.sdf
model.sdf如下：
true
0 0 1
15 15
100
50
false
0 0 1
15 15
model://my_ground_plane/materials/scripts
model://my_ground_plane/materials/textures/
MyGroundPlane/Image
第六步：在my_ground_plane文件夹下，创建文件model.config，内容如下：
My Ground Plane
1.0
model.sdf
My textured ground plane.
在gazebo中导入自己的地板模型
打开gazebo：
roslaunch turtlebot_gazebo turtlebot_world.launch
在另一个终端输入下面命令打开rviz：
roslaunch turtlebot_rviz_launchers view_robot.launch --screen
点击gazebo左上角的insert插入刚才建的模型：
选择My Ground Plane：
左键点击一下然后移动鼠标拖进去：
右键models列表里删除除了自己建的地板和机器人以外的其他家具：
用gazebo的移动工具，将机器人放到线上：
用gazebo的旋转工具将机器人的摄像机对准黄线：
旋转蓝色那条，让机器人绕z轴旋转，并对准：
写脚本控制机器人巡线
创建ros工作区间
mkdir -p ~/turtlebot_ws/src
cd ~/turtlebot_ws
catkin_init_workspace
cd src
catkin_create_pkg turtlebot1 rospy geometry_msgs sensor_msgs
cd ..
catkin_make
source ./devel/setup.bash
写过滤黄线的脚本
这里使用hsv提取黄线
先百度搜索黄色的hsv最大最小值：
在turtlebot1包的src下写过滤脚本follower_color_filter.py
cd src/turtlebot1/src
vi follower_color_filter.py
rosrun turtlebot1 follower_color_filter.py
follower_color_filter.py如下：
#!/usr/bin/env python
# BEGIN ALL
import rospy, cv2, cv_bridge, numpy
from sensor_msgs.msg import Image
class Follower:
def __init__(self):
self.bridge = cv_bridge.CvBridge()
cv2.namedWindow("window", 1)
self.image_sub = rospy.Subscriber('camera/rgb/image_raw',
Image, self.image_callback)
def image_callback(self, msg):
# BEGIN BRIDGE
image = self.bridge.imgmsg_to_cv2(msg)
cv2.imshow("ori", image )
# END BRIDGE
# BEGIN HSV
hsv = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)
cv2.imshow("hsv", hsv )
# END HSV
# BEGIN FILTER
lower_yellow = numpy.array([ 26, 43, 46])
upper_yellow = numpy.array([34, 255, 255])
mask = cv2.inRange(hsv, lower_yellow, upper_yellow)
# END FILTER
masked = cv2.bitwise_and(image, image, mask=mask)
cv2.imshow("window2", mask )
cv2.waitKey(3)
rospy.init_node('follower')
follower = Follower()
rospy.spin()
# END ALL
运行效果：
可以看到very nice!!!
写巡线脚本
vi follower_line.py
rosrun turtlebot1 follower_line.py
#!/usr/bin/env python
# BEGIN ALL
import rospy, cv2, cv_bridge, numpy
from sensor_msgs.msg import Image
from geometry_msgs.msg import Twist
class Follower:
def __init__(self):
self.bridge = cv_bridge.CvBridge()
cv2.namedWindow("window", 1)
self.image_sub = rospy.Subscriber('camera/rgb/image_raw',
Image, self.image_callback)
self.cmd_vel_pub = rospy.Publisher('cmd_vel_mux/input/teleop',
Twist, queue_size=1)
self.twist = Twist()
def image_callback(self, msg):
image = self.bridge.imgmsg_to_cv2(msg,desired_encoding='bgr8')
hsv = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)
lower_yellow = numpy.array([ 26, 43, 46])
upper_yellow = numpy.array([34, 255, 255])
mask = cv2.inRange(hsv, lower_yellow, upper_yellow)
h, w, d = image.shape
search_top = 3*h/4
search_bot = 3*h/4 + 20
mask[0:search_top, 0:w] = 0
mask[search_bot:h, 0:w] = 0
M = cv2.moments(mask)
if M['m00'] > 0:
cx = int(M['m10']/M['m00'])
cy = int(M['m01']/M['m00'])
cv2.circle(image, (cx, cy), 20, (0,0,255), -1)
# BEGIN CONTROL
err = cx - w/2
self.twist.linear.x = 0.2
self.twist.angular.z = -float(err) / 100
self.cmd_vel_pub.publish(self.twist)
# END CONTROL
cv2.imshow("window", image)
cv2.waitKey(3)
rospy.init_node('follower')
follower = Follower()
rospy.spin()
# END ALL
运行脚本：
总结
挺好玩的吧，可以仿真下巡线的算法哈哈哈哈，做过智能车的小伙伴应该不陌生哦～
enjoy it~