1.创建包
mkdir -p catkin_ws/src
cd catkin_ws/src
catkin_create_pkg learning_tf tf roscpp rospy turtlesim
建立你的新包roscd之前:
cd ~/catkin_ws
catkin_make
source ./devel/setup.bash
这时功能包就已经构建完成了。
此时打开Roboware studio 在/learning_tf/src下编写TF广播器(turtle_tf_broadcaster.cpp ):
#include <ros/ros.h>
#include <tf/transform_broadcaster.h>
#include <turtlesim/Pose.h>
std::string turtle_name;
void poseCallback(const turtlesim::PoseConstPtr& msg){
static tf::TransformBroadcaster br;
tf::Transform transform;
transform.setOrigin( tf::Vector3(msg->x, msg->y, 0.0) );
tf::Quaternion q;
q.setRPY(0, 0, msg->theta);
transform.setRotation(q);
br.sendTransform(tf::StampedTransform(transform, ros::Time::now(), "world", turtle_name));
}
int main(int argc, char** argv){
ros::init(argc, argv, "my_tf_broadcaster");
if (argc != 2){ROS_ERROR("need turtle name as argument"); return -1;};
turtle_name = argv[1];
ros::NodeHandle node;
ros::Subscriber sub = node.subscribe(turtle_name+"/pose", 10, &poseCallback);
ros::spin();
return 0;
};
需要说明的是,在创建cpp文件时应该是添加到可执行的文件这一选项。
打开CMakLists.txt文件,并添加以下行:
add_executable(turtle_tf_broadcaster src/turtle_tf_broadcaster.cpp)
target_link_libraries(turtle_tf_broadcaster ${catkin_LIBRARIES})
在/learning_tf/src下编写TF监听器(turtle_tf_listener.cpp)
#include <ros/ros.h>
#include <tf/transform_listener.h>
#include <geometry_msgs/Twist.h>
#include <turtlesim/Spawn.h>
int main(int argc, char** argv){
ros::init(argc, argv, "my_tf_listener");
ros::NodeHandle node;
ros::service::waitForService("spawn");
ros::ServiceClient add_turtle =
node.serviceClient<turtlesim::Spawn>("spawn");
turtlesim::Spawn srv;
add_turtle.call(srv);
ros::Publisher turtle_vel =
node.advertise<geometry_msgs::Twist>("turtle2/cmd_vel", 10);
tf::TransformListener listener;
ros::Rate rate(10.0);
while (node.ok()){
tf::StampedTransform transform;
try{
listener.lookupTransform("/turtle2", "/turtle1",
ros::Time(0), transform);
}
catch (tf::TransformException &ex) {
ROS_ERROR("%s",ex.what());
ros::Duration(1.0).sleep();
continue;
}
geometry_msgs::Twist vel_msg;
vel_msg.angular.z = 4.0 * atan2(transform.getOrigin().y(),
transform.getOrigin().x());
vel_msg.linear.x = 0.5 * sqrt(pow(transform.getOrigin().x(), 2) +
pow(transform.getOrigin().y(), 2));
turtle_vel.publish(vel_msg);
rate.sleep();
}
return 0;
};
打开CMakLists.txt文件,并添加以下行:
add_executable(turtle_tf_listener src/turtle_tf_listener.cpp)
target_link_libraries(turtle_tf_listener ${catkin_LIBRARIES})
在leanring_tf下创建launch文件:
mkdir launch
在roboware中创建launch文件start_demo.launch
<launch>
<!-- Turtlesim Node-->
<node pkg="turtlesim" type="turtlesim_node" name="sim"/>
<node pkg="turtlesim" type="turtle_teleop_key" name="teleop" output="screen"/>
<!-- Axes -->
<param name="scale_linear" value="2" type="double"/>
<param name="scale_angular" value="2" type="double"/>
<node pkg="learning_tf" type="turtle_tf_broadcaster"
args="/turtle1" name="turtle1_tf_broadcaster" />
<node pkg="learning_tf" type="turtle_tf_broadcaster"
args="/turtle2" name="turtle2_tf_broadcaster" />
<node pkg="learning_tf" type="turtle_tf_listener"
name="listener" />
</launch>
保存好所有的文件后在终端中进入:
cd catkin_ws
catkin_make
source ./devel/setup.bash
然后再运行:
roslaunch learning_tf start_demo.launch
这时就可以看到两只turtle了,也就是最开始见到的跟随效果。