ROS actionlib学习

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   下面这个例子将展示用actionlib来计算随机变量的均值和标准差。首先在action文件中定义goal、result和feedback的数据类型,其中goal为样本容量,result为均值和标准差,feedback为样本编号、当前样本数据、均值和标准差。

#goal definition
int32 samples
---
#result definition
float32 mean
float32 std_dev
---
#feedback
int32 sample
float32 data
float32 mean
float32 std_dev

  按照之前例程中的步骤修改CMakeLists.txt后进行编译,生成相关的消息文件和头文件。

 

 Writing a Simple Server 

   参考 C++ SimpleActionServer 文档,SimpleActionServer类的构造函数有多种重载形式:

SimpleActionServer (std::string name, ExecuteCallback execute_callback, bool auto_start)
 
SimpleActionServer (std::string name, bool auto_start)

SimpleActionServer (ros::NodeHandle n, std::string name, ExecuteCallback execute_callback, bool auto_start)

SimpleActionServer (ros::NodeHandle n, std::string name, bool auto_start)

  在Writing a Simple Action Server using the Execute Callback的例子中,SimpleActionServer就使用了上面第3种构造函数,参数为节点句柄、action名称以及ExecuteCallback回调函数。在本例中没有使用这种来创建action server,而是在action server创建后通过注册 goal callback 和 preempt callback这两个回调函数来处理事件。

void  registerGoalCallback (boost::function< void()> cb)     // Allows users to register a callback to be invoked when a new goal is available
 
void  registerPreemptCallback (boost::function< void()> cb)  // Allows users to register a callback to be invoked when a new preempt request is available

 

   服务端代码averaging_server.cpp如下:

#include <ros/ros.h>
#include <std_msgs/Float32.h>
#include <actionlib/server/simple_action_server.h>  // actionlib/server/simple_action_server.h is the action library used from implementing simple actions
#include <actionlib_tutorials/AveragingAction.h>   // This includes action message generated from the Averaging.action file

class AveragingAction
{
public:
    
  AveragingAction(std::string name) : 
    as_(nh_, name, false),
    action_name_(name)
  {
    //register the goal and feeback callbacks
    as_.registerGoalCallback(boost::bind(&AveragingAction::goalCB, this));
    as_.registerPreemptCallback(boost::bind(&AveragingAction::preemptCB, this));

    //subscribe to the data topic of interest
    sub_ = nh_.subscribe("/random_number", 1, &AveragingAction::analysisCB, this);
    as_.start();
  }

  ~AveragingAction(void)
  {
  }

  void goalCB()
  {
    // reset helper variables
    data_count_ = 0;
    sum_ = 0;
    sum_sq_ = 0;
    // accept the new goal
    goal_ = as_.acceptNewGoal()->samples;
  // acceptNewGoal: Accepts a new goal when one is available. The status of this goal is set to active upon acceptance, and the status of any previously active goal is set to preempted }
void preemptCB() { ROS_INFO("%s: Preempted", action_name_.c_str()); // set the action state to preempted as_.setPreempted(); } void analysisCB(const std_msgs::Float32::ConstPtr& msg) { // make sure that the action hasn\'t been canceled if (!as_.isActive()) return; data_count_++; feedback_.sample = data_count_; feedback_.data = msg->data; //compute the std_dev and mean of the data sum_ += msg->data; feedback_.mean = sum_ / data_count_; sum_sq_ += pow(msg->data, 2); feedback_.std_dev = sqrt(fabs((sum_sq_/data_count_) - pow(feedback_.mean, 2))); as_.publishFeedback(feedback_); if(data_count_ > goal_) { result_.mean = feedback_.mean; result_.std_dev = feedback_.std_dev; if(result_.mean < 5.0) { ROS_INFO("%s: Aborted", action_name_.c_str()); //set the action state to aborted as_.setAborted(result_); } else { ROS_INFO("%s: Succeeded", action_name_.c_str()); // set the action state to succeeded as_.setSucceeded(result_); } } } protected: ros::NodeHandle nh_; actionlib::SimpleActionServer<actionlib_tutorials::AveragingAction> as_; std::string action_name_; int data_count_, goal_; float sum_, sum_sq_; actionlib_tutorials::AveragingFeedback feedback_; actionlib_tutorials::AveragingResult result_; ros::Subscriber sub_; }; int main(int argc, char** argv) { ros::init(argc, argv, "averaging"); AveragingAction averaging(ros::this_node::getName()); ros::spin(); return 0; }

  程序中标准差是根据下面的公式计算的:

   服务端程序会订阅/random_number话题,并执行回调函数analysisCB。注意在消息回调函数的开头会调用SimpleActionServer类中的isActive()来检测goal的状态,如果不是处于active状态(The goal is currently being processed by the action server)则退出程序,直到客户端发起请求,goal开始被server处理。

  Goals请求由ActionClient发出,ActionServer接收后会创建一个有限状态机来跟踪goal的状态:  

  goal状态的转变主要由server端程序发起,可以使用下面一系列的命令:

  • setAccepted - After inspecting a goal, decide to start processing it

  • setRejected - After inspecting a goal, decide to never process it because it is an invalid request (out of bounds, resources not available, invalid, etc)

  • setSucceeded - Notify that goal has been successfully processed

  • setAborted - Notify that goal encountered an error during processsing, and had to be aborted

  • setCanceled - Notify that goal is no longer being processed, due to a cancel request

  客户端也能异步发起状态转变:

  • CancelRequest: The client notifies the action server that it wants the server to stop processing the goal.

  状态机有下面多种状态:

  中间状态:

  • Pending - The goal has yet to be processed by the action server

  • Active - The goal is currently being processed by the action server

  • Recalling - The goal has not been processed and a cancel request has been received from the action client, but the action server has not confirmed the goal is canceled

  • Preempting - The goal is being processed, and a cancel request has been received from the action client, but the action server has not confirmed the goal is canceled

  最终状态:

  • Rejected - The goal was rejected by the action server without being processed and without a request from the action client to cancel

  • Succeeded - The goal was achieved successfully by the action server

  • Aborted - The goal was terminated by the action server without an external request from the action client to cancel

  • Recalled - The goal was canceled by either another goal, or a cancel request, before the action server began processing the goal

  • Preempted - Processing of the goal was canceled by either another goal, or a cancel request sent to the action server

 

 Writing the Data Node 

  发布随机数节点的代码 gen_numbers.py如下。Python中的random.normalvariate(mu, sigma)函数会返回服从正态分布的随机数,均值为mu,标准差为sigma.

#!/usr/bin/env python

import rospy
from std_msgs.msg import Float32
import random
def gen_number():
    pub = rospy.Publisher(\'random_number\', Float32)
    rospy.init_node(\'random_number_generator\', log_level=rospy.INFO)
    rospy.loginfo("Generating random numbers")

    while not rospy.is_shutdown():
        pub.publish(Float32(random.normalvariate(5, 1)))
        rospy.sleep(0.05)

if __name__ == \'__main__\':
  try:
    gen_number()
  except Exception, e:
    print "done"

  注意不要忘记给文件添加可执行权限:

chmod +x gen_numbers.py

 

 Writing a Threaded Simple Action Client 

   SimpleActionClient的构造函数如下,注意参数spin_thread的设置。如果spin_thread为false则需要自行开启线程。

// Constructs a SingleGoalActionClient 
actionlib::SimpleActionClient< ActionSpec >::SimpleActionClient ( const std::string & name, bool spin_thread = true )

/*
Parameters 
name: The action name. Defines the namespace in which the action communicates 
spin_thread: If true, spins up a thread to service this action\'s subscriptions. 
             If false, then the user has to call ros::spin() themselves. Defaults to True
*/

  客户端程序averaging_client.cpp如下:

#include <ros/ros.h>
#include <actionlib/client/simple_action_client.h>  // the action library used from implementing simple action clients
#include <actionlib/client/terminal_state.h>        // defines the possible goal states
#include <actionlib_tutorials/AveragingAction.h>    // This includes action message generated from the Averaging.action file
#include <boost/thread.hpp>                          // the boost thread library for spinning the thread

void spinThread()
{
  ros::spin();
}

int main (int argc, char **argv)
{
  ros::init(argc, argv, "test_averaging");

  // create the action client
  actionlib::SimpleActionClient<actionlib_tutorials::AveragingAction> ac("averaging", false);
  
  boost::thread spin_thread(&spinThread); // the thread is created and the ros node is started spinning in the background

  ROS_INFO("Waiting for action server to start.");
  // Since the action server may not be up and running, the action client will wait for the action server to start before continuing.
  ac.waitForServer(); 

  ROS_INFO("Action server started, sending goal.");
  // send a goal to the action
  actionlib_tutorials::AveragingGoal goal;
  goal.samples = 100;
  ac.sendGoal(goal);

  // The action client now waits for the goal to finish before continuing 
  bool finished_before_timeout = ac.waitForResult(ros::Duration(30.0)); 

  if (finished_before_timeout)
  {
    actionlib::SimpleClientGoalState state = ac.getState();
    ROS_INFO("Action finished: %s",state.toString().c_str());
  }
  else
    ROS_INFO("Action did not finish before the time out.");

  // shutdown the node and join the thread back before exiting
  ros::shutdown();
  
  spin_thread.join();

  //exit
  return 0;
}

  下面是boost::thread线程管理的一个例子:

#include <boost/thread.hpp> 
#include <iostream> 

void wait(int seconds) 
{ 
  boost::this_thread::sleep(boost::posix_time::seconds(seconds)); 
} 

void thread() 
{ 
  for (int i = 0; i < 5; ++i) 
  { 
    wait(1); 
    std::cout << i << std::endl; 
  } 
} 

int main() 
{ 
  boost::thread t(thread); 
  t.join(); 

  return 0;
} 

  上述示例中的变量t 一旦被创建,该thread()函数就在其所在线程中被立即执行。为了防止程序终止,就需要对新建线程调用 join() 方法。 join() 方法是一个阻塞调用:它可以暂停当前线程,直到调用 join() 的线程运行结束。 这就使得main() 函数一直会等待到 thread() 运行结束。程序输出如下图所示,如果没有用join方法,则会直接退出。

 

 

 Running an Action Server and Client with Other Nodes 

   运行server:

rosrun actionlib_tutorials averaging_server

  运行随机数发生器节点:

rosrun actionlib_tutorials gen_numbers.py

  运行client:

rosrun actionlib_tutorials averaging_client

  计算平均数时查看feedback:

rostopic echo /averaging/feedback 

 

 

参考:

actionlib-Tutorials

boost::thread线程管理

ROS actionlib学习(一)

ROS actionlib学习(二)

actionlib-Detailed Description

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