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 python

import roslib; roslib.load_manifest('rbx1_nav')
import rospy
import actionlib
from actionlib_msgs.msg import *
from geometry_msgs.msg import Pose, PoseWithCovarianceStamped, Point, Quaternion, Twist
from move_base_msgs.msg import MoveBaseAction, MoveBaseGoal
from random import sample
from math import pow, sqrt

class 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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