ROS探索总结（十五）——amcl（导航与定位）

        在理解了move_base的基础上，我们开始机器人的定位与导航。gmaping包是用来生成地图的，需要使用实际的机器人获取激光或者深度数据，所以我们先在已有的地图上进行导航与定位的仿真。

        amcl是移动机器人二维环境下的概率定位系统。它实现了自适应（或kld采样）的蒙特卡罗定位方法，其中针对已有的地图使用粒子滤波器跟踪一个机器人的姿态。

一、测试

        首先运行机器人节点：

roslaunch rbx1_bringup fake_turtlebot.launch

        然后运行amcl节点，使用测试地图：        

roslaunch rbx1_nav fake_amcl.launch map:=test_map.yaml

        可以看一下fake_amcl.launch这个文件的内容：

<launch>  <!-- Set the name of the map yaml file: can be overridden on the command line. -->  <arg name="map" default="test_map.yaml" />  <!-- Run the map server with the desired map -->  <node name="map_server" pkg="map_server" type="map_server" args="$(find rbx1_nav)/maps/$(arg map)"/>  <!-- The move_base node -->  <include file="$(find rbx1_nav)/launch/fake_move_base.launch" />    <!-- Run fake localization compatible with AMCL output -->  <node pkg="fake_localization" type="fake_localization"  name="fake_localization" output="screen" />  <!-- For fake localization we need static transforms between /odom and /map and /map and /world -->  <node pkg="tf" type="static_transform_publisher" name="odom_map_broadcaster" args="0 0 0 0 0 0 /odom /map 100" /></launch>

         这个lanuch文件作用是加载地图，并且调用fake_move_base.launch文件打开move_base节点并加载配置文件，最后运行amcl。
         然后运行rviz：

rosrun rviz rviz -d `rospack find rbx1_nav`/nav_fuerte.vcg

         这时在rvoiz中就应该显示出了地图和机器人：

        现在就可以通过rviz在地图上选择目标位置了，然后就会看到机器人自动规划出一条全局路径，并且导航前进：

二、自主导航 

        在实际应用中，我们往往希望机器人能够自主进行定位和导航，不需要认为的干预，这样才更智能化。在这一节的测试中，我们让目标点在地图中随机生成，然后机器人自动导航到达目标。
        这里运行的主要文件是：fake_nav_test.launch，让我们来看一下这个文件的内容：   

<launch>  <param name="use_sim_time" value="false" />  <!-- Start the ArbotiX controller -->  <include file="$(find rbx1_bringup)/launch/fake_turtlebot.launch" />  <!-- Run the map server with the desired map -->  <node name="map_server" pkg="map_server" type="map_server" args="$(find rbx1_nav)/maps/test_map.yaml"/>  <!-- The move_base node -->  <node pkg="move_base" type="move_base" respawn="false" name="move_base" output="screen">    <rosparam file="$(find rbx1_nav)/config/fake/costmap_common_params.yaml" command="load" ns="global_costmap" />    <rosparam file="$(find rbx1_nav)/config/fake/costmap_common_params.yaml" command="load" ns="local_costmap" />    <rosparam file="$(find rbx1_nav)/config/fake/local_costmap_params.yaml" command="load" />    <rosparam file="$(find rbx1_nav)/config/fake/global_costmap_params.yaml" command="load" />    <rosparam file="$(find rbx1_nav)/config/fake/base_local_planner_params.yaml" command="load" />    <rosparam file="$(find rbx1_nav)/config/nav_test_params.yaml" command="load" />  </node>    <!-- Run fake localization compatible with AMCL output -->  <node pkg="fake_localization" type="fake_localization" name="fake_localization" output="screen" />    <!-- For fake localization we need static transform between /odom and /map -->  <node pkg="tf" type="static_transform_publisher" name="map_odom_broadcaster" args="0 0 0 0 0 0 /map /odom 100" />    <!-- Start the navigation test -->  <node pkg="rbx1_nav" type="nav_test.py" name="nav_test" output="screen">    <param name="rest_time" value="1" />    <param name="fake_test" value="true" />  </node>  </launch>

        这个lanuch的功能比较多：
      （1） 加载机器人驱动
      （2） 加载地图
      （3） 启动move_base节点，并且加载配置文件
      （4） 运行amcl节点
      （5） 然后加载nav_test.py执行文件，进行随机导航
        相当于是把我们之前实验中的多个lanuch文件合成了一个文件。
        现在开始进行测试，先运行ROS：

roscore

        然后我们运行一个监控的窗口，可以实时看到机器人发送的数据：

rxconsole

        接着运行lanuch文件，并且在一个新的终端中打开rviz：

roslaunch rbx1_nav fake_nav_test.launch（打开新终端）rosrun rviz rviz -d `rospack find rbx1_nav`/nav_test_fuerte.vcg

        好了，此时就看到了机器人已经放在地图当中了。然后我们点击rviz上的“2D Pose Estimate”按键，然后左键在机器人上单击，让绿色的箭头和黄色的箭头重合，机器人就开始随机选择目标导航了：

        

         在监控窗口中，我们可以看到机器人发送的状态信息：

        其中包括距离信息、状态信息、目标的编号、成功率和速度等信息。

三、导航代码分析

#!/usr/bin/env pythonimport roslib; roslib.load_manifest('rbx1_nav')import rospyimport actionlibfrom actionlib_msgs.msg import *from geometry_msgs.msg import Pose, PoseWithCovarianceStamped, Point, Quaternion, Twistfrom move_base_msgs.msg import MoveBaseAction, MoveBaseGoalfrom random import samplefrom math import pow, sqrtclass NavTest():    def __init__(self):        rospy.init_node('nav_test', anonymous=True)                rospy.on_shutdown(self.shutdown)                # How long in seconds should the robot pause at each location?        # 在每个目标位置暂停的时间        self.rest_time = rospy.get_param("~rest_time", 10)                # Are we running in the fake simulator?        # 是否仿真？        self.fake_test = rospy.get_param("~fake_test", False)                # Goal state return values        # 到达目标的状态        goal_states = ['PENDING', 'ACTIVE', 'PREEMPTED',                        'SUCCEEDED', 'ABORTED', 'REJECTED',                       'PREEMPTING', 'RECALLING', 'RECALLED',                       'LOST']                # Set up the goal locations. Poses are defined in the map frame.          # An easy way to find the pose coordinates is to point-and-click        # Nav Goals in RViz when running in the simulator.        # Pose coordinates are then displayed in the terminal        # that was used to launch RViz.        # 设置目标点的位置        # 如果想要获得某一点的坐标，在rviz中点击 2D Nav Goal 按键，然后单机地图中一点        # 在终端中就会看到坐标信息        locations = dict()                locations['hall_foyer'] = Pose(Point(0.643, 4.720, 0.000), Quaternion(0.000, 0.000, 0.223, 0.975))        locations['hall_kitchen'] = Pose(Point(-1.994, 4.382, 0.000), Quaternion(0.000, 0.000, -0.670, 0.743))        locations['hall_bedroom'] = Pose(Point(-3.719, 4.401, 0.000), Quaternion(0.000, 0.000, 0.733, 0.680))        locations['living_room_1'] = Pose(Point(0.720, 2.229, 0.000), Quaternion(0.000, 0.000, 0.786, 0.618))        locations['living_room_2'] = Pose(Point(1.471, 1.007, 0.000), Quaternion(0.000, 0.000, 0.480, 0.877))        locations['dining_room_1'] = Pose(Point(-0.861, -0.019, 0.000), Quaternion(0.000, 0.000, 0.892, -0.451))                # Publisher to manually control the robot (e.g. to stop it)        # 发布控制机器人的消息        self.cmd_vel_pub = rospy.Publisher('cmd_vel', Twist)                # Subscribe to the move_base action server        # 订阅move_base服务器的消息        self.move_base = actionlib.SimpleActionClient("move_base", MoveBaseAction)                rospy.loginfo("Waiting for move_base action server...")                # Wait 60 seconds for the action server to become available        # 60s等待时间限制        self.move_base.wait_for_server(rospy.Duration(60))                rospy.loginfo("Connected to move base server")                # A variable to hold the initial pose of the robot to be set by         # the user in RViz        # 保存机器人的在rviz中的初始位置        initial_pose = PoseWithCovarianceStamped()                # Variables to keep track of success rate, running time,        # and distance traveled        # 保存成功率、运行时间、和距离的变量        n_locations = len(locations)        n_goals = 0        n_successes = 0        i = n_locations        distance_traveled = 0        start_time = rospy.Time.now()        running_time = 0        location = ""        last_location = ""                # Get the initial pose from the user        # 获取初始位置(仿真中可以不需要)        rospy.loginfo("*** Click the 2D Pose Estimate button in RViz to set the robot's initial pose...")        rospy.wait_for_message('initialpose', PoseWithCovarianceStamped)        self.last_location = Pose()        rospy.Subscriber('initialpose', PoseWithCovarianceStamped, self.update_initial_pose)                # Make sure we have the initial pose        # 确保有初始位置        while initial_pose.header.stamp == "":            rospy.sleep(1)                    rospy.loginfo("Starting navigation test")                # Begin the main loop and run through a sequence of locations        # 开始主循环，随机导航        while not rospy.is_shutdown():            # If we've gone through the current sequence,            # start with a new random sequence            # 如果已经走完了所有点，再重新开始排序            if i == n_locations:                i = 0                sequence = sample(locations, n_locations)                # Skip over first location if it is the same as                # the last location                # 如果最后一个点和第一个点相同，则跳过                if sequence[0] == last_location:                    i = 1                        # Get the next location in the current sequence            # 在当前的排序中获取下一个目标点            location = sequence[i]                                    # Keep track of the distance traveled.            # Use updated initial pose if available.            # 跟踪形式距离            # 使用更新的初始位置            if initial_pose.header.stamp == "":                distance = sqrt(pow(locations[location].position.x -                                     locations[last_location].position.x, 2) +                                pow(locations[location].position.y -                                     locations[last_location].position.y, 2))            else:                rospy.loginfo("Updating current pose.")                distance = sqrt(pow(locations[location].position.x -                                     initial_pose.pose.pose.position.x, 2) +                                pow(locations[location].position.y -                                     initial_pose.pose.pose.position.y, 2))                initial_pose.header.stamp = ""                        # Store the last location for distance calculations            # 存储上一次的位置，计算距离            last_location = location                        # Increment the counters            # 计数器加1            i += 1            n_goals += 1                    # Set up the next goal location            # 设定下一个目标点            self.goal = MoveBaseGoal()            self.goal.target_pose.pose = locations[location]            self.goal.target_pose.header.frame_id = 'map'            self.goal.target_pose.header.stamp = rospy.Time.now()                        # Let the user know where the robot is going next            # 让用户知道下一个位置            rospy.loginfo("Going to: " + str(location))                        # Start the robot toward the next location            # 向下一个位置进发            self.move_base.send_goal(self.goal)                        # Allow 5 minutes to get there            # 五分钟时间限制            finished_within_time = self.move_base.wait_for_result(rospy.Duration(300))                         # Check for success or failure            # 查看是否成功到达            if not finished_within_time:                self.move_base.cancel_goal()                rospy.loginfo("Timed out achieving goal")            else:                state = self.move_base.get_state()                if state == GoalStatus.SUCCEEDED:                    rospy.loginfo("Goal succeeded!")                    n_successes += 1                    distance_traveled += distance                    rospy.loginfo("State:" + str(state))                else:                  rospy.loginfo("Goal failed with error code: " + str(goal_states[state]))                        # How long have we been running?            # 运行所用时间            running_time = rospy.Time.now() - start_time            running_time = running_time.secs / 60.0                        # Print a summary success/failure, distance traveled and time elapsed            # 输出本次导航的所有信息            rospy.loginfo("Success so far: " + str(n_successes) + "/" +                           str(n_goals) + " = " +                           str(100 * n_successes/n_goals) + "%")            rospy.loginfo("Running time: " + str(trunc(running_time, 1)) +                           " min Distance: " + str(trunc(distance_traveled, 1)) + " m")            rospy.sleep(self.rest_time)                def update_initial_pose(self, initial_pose):        self.initial_pose = initial_pose    def shutdown(self):        rospy.loginfo("Stopping the robot...")        self.move_base.cancel_goal()        rospy.sleep(2)        self.cmd_vel_pub.publish(Twist())        rospy.sleep(1)      def trunc(f, n):    # Truncates/pads a float f to n decimal places without rounding    slen = len('%.*f' % (n, f))    return float(str(f)[:slen])if __name__ == '__main__':    try:        NavTest()        rospy.spin()    except rospy.ROSInterruptException:        rospy.loginfo("AMCL navigation test finished.")

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