TurtleBot3 循线机器人

提示：文章写完后，目录可以自动生成，如何生成可参考右边的帮助文档

---

前言

由于时代的更替，TurtleBot系列以及更新了很多代了，TurtleBot1支持的是Ubuntu16.04，然而Unbntu18.04大家用的比较多，因此，我选择用三代来实现本次的功能。

---

一、按装TurtleBot3

1. 创建工作区以及包

（1）创建wanderbot_ws工作区

mkdir -p ~/wanderbot_ws/src
cd ~/wanderbot_ws/src
catkin_init_workspace

（2）创建wanderbot包

cd ~/wanderbot_ws/src
catkin_create_pkg wanderbot rospy geometry_msgs sensor_msgs

2.安装过程
（1）安装Turtlebot3以及仿真环境

cd wanderbot_ws/src
git clone https://github.com/ROBOTIS-GIT/turtlebot3_msgs.git
git clone https://github.com/ROBOTIS-GIT/turtlebot3.git
git clone https://github.com/ROBOTIS-GIT/turtlebot3_simulations.git

（2）安装gmapping包

cd wanderbot_ws/src
git clone https://github.com/ros-perception/openslam_gmapping.git
git clone https://github.com/ros-perception/slam_gmapping.git
git clone https://github.com/ros-planning/navigation.git
git clone https://github.com/ros/geometry2.git
git clone https://github.com/ros-planning/navigation_msgs.git

3.编译

cd ~/wanderbot_ws
catkin_make

二、传感器的使用

（1）打开世界地图

roslaunch turtlebot3_gazebo turtlebot3_world.launch

（2）启动仿真环境

roslaunch turtlebot3_gazebo turtlebot3_world.launch

如果遇到这中bug

（RLException: Invalid <arg> tag: environment variable 'TURTLEBOT3_MODEL' is not set. Arg xml is <arg default="$(env TURTLEBOT3_MODEL)" doc="model type [burger, waffle, waffle_pi]" name="model"/>
The traceback for the exception was written to the log file）*  

解决bug方法：

export TURTLEBOT3_MODEL=burger

（3）DepthCloud选项

bash 显示深度相机数据

（4）Image选项

显示深度图片或者rgb图片

选择话题为深度图片

三、循线设计

1.用自定义的图片设计gazebo的地板
（1）在主目录下Ctrl+h，打开隐藏文件
（2）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

（3）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
              }
            }
          }
        }

（4）在textures下保存我们想要的地板图片Myimage.png
如图，将它当到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/

（5）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内容如下：

<?xml version="1.0" encoding="UTF-8"?>
<sdf version="1.4">
   <model name="my_ground_plane">
      <static>true</static>
      <link name="link">
         <collision name="collision">
            <geometry>
               <plane>
                  <normal>0 0 1</normal>
                  <size>15 15</size>
               </plane>
            </geometry>
            <surface>
               <friction>
                  <ode>
                     <mu>100</mu>
                     <mu2>50</mu2>
                  </ode>
               </friction>
            </surface>
         </collision>
         <visual name="visual">
            <cast_shadows>false</cast_shadows>
            <geometry>
               <plane>
                  <normal>0 0 1</normal>
                  <size>15 15</size>
               </plane>
            </geometry>
            <material>
               <script>
                  <uri>model://my_ground_plane/materials/scripts</uri>
                  <uri>model://my_ground_plane/materials/textures/</uri>
                  <name>MyGroundPlane/Image</name>
               </script>
            </material>
         </visual>
      </link>
   </model>
</sdf>

（6)在my_ground_plane文件夹下，创建文件moderl.config，内容如下：

<?xml version="1.0" encoding="UTF-8"?>
<model>
   <name>My Ground Plane</name>
   <version>1.0</version>
   <sdf version="1.4">model.sdf</sdf>
   <description>My textured ground plane.</description>
</model>

2.在gazebo中导入自己的地板模型
（1) 打开gazebo：

roslaunch turtlebot3_gazebo turtlebot3_world.launch

（2）另一个打开rviz：

roslaunch turtlebot_rviz_launchers view_robot.launch --screen

（3）点击gazebo左上角的insert插入刚才建的模型
（4）选择My Ground Plane:

（5）用鼠标左键点击一下然后拖进去，右键gazebo中的模型del掉除了机器人和自己搭建的地板以外的其他模型
（6）用gazebo的移动、旋转工具将机器人放到线上面

四、循线脚本

1.写脚本控制机器人巡线
（1)创建ros工作空间

mkdir -p ~/turtlebot_ws/src
cd ~/turtlebot_ws
catkin_init_workspace
cd ..
catkin_make
cd ~/turtlebot_ws/src
catkin_create_pkg turtlebot1 rospy geometry_msgs sensor_msgs
cd ..
source ./devel/setup.bash

(2)
2.1写过滤黄线的脚本

cd src/turtlebot1/src
vi follower_color_filter.py

follower_color_filter.py内容如下：

#!/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

2.2给follower_color_filter.py脚本授权，编译

chmod 777 follower_color_filter.py
cd ~/turtlebot_ws
catkin_make

2.3运行脚本（在第2节的基础上进行）

rosrun turtlebot1 follower_color_filter.py

运行效果：

（3）写巡线脚本

vi follower_line.py
rosrun turtlebot1 follower_line.py

follower_line.py内容如下：

#!/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

授权脚本权限以及编译步骤与2.1类似

运行脚本：

rosrun turtlebot1 follower_line.py

运行效果如下：

总结

本章内容是针对于《ROS机器人编程实践》中TurtleBot机器人循线部分的内容。
希望对广大读者有一些帮助，在过程中遇到各种问题可以留言或者私信我。感谢大家的支持！
本次内容参考多人的博客内容改编，若有侵权，请及时告之，立马删除！