用毫米波雷达数据做ＳＬＡＭ

遇到的问题，目前的毫米波雷达数据很稀疏，用ｅｘｃｅｌ存储，需要转换过去，测试一下当前的激光雷达算法，并测试。

rosbag数据用ｍａｔｌａｂ(linux版本）可以方便的查看变量和ｔｏｐｉｃ

一. 第一步，用激光雷达数据测试

[转载自：https://blog.csdn.net/fk1174/article/details/52673413】

第二种办法，首先去http://kaspar.informatik.uni-freiburg.de/~slamEvaluation/datasets.php下载数据集，我用的是Intel Research Lab 的数据集，保存为intel.clf。（clf是一种日志存储格式）

怎么下载呢？运行这语句就可以了。

wget http://ais.informatik.uni-freiburg.de/slamevaluation/datasets/aces.clf

编写把clf文件转化为rosbag文件的python脚本：

#!/usr/bin/env python


'''This is a converter for the Intel Research Lab SLAM dataset
   ( http://kaspar.informatik.uni-freiburg.de/~slamEvaluation/datasets/intel.clf )
   to rosbag'''

import rospy
import rosbag
from sensor_msgs.msg import LaserScan
from nav_msgs.msg import Odometry
from math import pi
from tf2_msgs.msg import TFMessage
from geometry_msgs.msg import TransformStamped
import tf

def make_tf_msg(x, y, theta, t,base,base0):
    trans = TransformStamped()
    trans.header.stamp = t
    trans.header.frame_id = base
    trans.child_frame_id = base0
    trans.transform.translation.x = x
    trans.transform.translation.y = y
    q = tf.transformations.quaternion_from_euler(0, 0, theta)
    trans.transform.rotation.x = q[0]
    trans.transform.rotation.y = q[1]
    trans.transform.rotation.z = q[2]
    trans.transform.rotation.w = q[3]

    msg = TFMessage()
    msg.transforms.append(trans)
    return msg

with open('/home/kylefan/catkin_ws/data/intel/intel.clf') as dataset:
    with rosbag.Bag('/home/kylefan/intel.bag', 'w') as bag:
        for line in dataset.readlines():
            line = line.strip()
            tokens = line.split(' ')
            if len(tokens) <= 2:
                continue
            if tokens[0] == 'FLASER':
                msg = LaserScan()
                num_scans = int(tokens[1])

                if num_scans != 180 or len(tokens) < num_scans + 9:
                    rospy.logwarn("unsupported scan format")
                    continue

                msg.header.frame_id = 'base_link'
                t = rospy.Time(float(tokens[(num_scans + 8)]))
                msg.header.stamp = t
                msg.angle_min = -90.0 / 180.0 * pi
                msg.angle_max = 90.0 / 180.0 * pi
                msg.angle_increment = pi / num_scans
                msg.time_increment = 0.2 / 360.0
                msg.scan_time = 0.2
                msg.range_min = 0.001
                msg.range_max = 50.0
                msg.ranges = [float(r) for r in tokens[2:(num_scans + 2)]]

                bag.write('scan', msg, t)

                odom_x, odom_y, odom_theta = [float(r) for r in tokens[(num_scans + 2):(num_scans + 5)]]
                tf_msg = make_tf_msg(odom_x, odom_y, odom_theta, t,'base_link','base_laser_link')
                bag.write('tf', tf_msg, t)

            elif tokens[0] == 'ODOM':
                odom_x, odom_y, odom_theta = [float(t) for t in tokens[1:4]]
                t = rospy.Time(float(tokens[7]))
                tf_msg = make_tf_msg(odom_x, odom_y, odom_theta, t,'odom','base_link')
                bag.write('tf', tf_msg, t)

保存为bag.py，放到ros包beginner_tutorials的scripts文件夹下，然后：

chmod +x bag.py

在这之前，需要建立好ｂｅｇｉｎｎｅｒ_tutorialｓ的ｐａｃｋａｇｅ,然后：source ./devel/setup.bash

rosrun beginner_tutorials bag.py

就把激光和odom的数据按照真实的时间点写入到了intel.bag里了。

最后

rosbag play intel.bag

激光的数据就发布到/laser了，这样就实现模拟的作用了。

这时候想再rviz里看看，记得要在左上角Global Options里面设置/odom为fixed的：

参考大神：http://answers.ros.org/question/233042/in-ros-gmapping-how-to-use-intel-research-lab-dataset/

 

具体怎么运行呢？

1. Bring up the master:

   roscore

2. Make sure that use_sim_time is set to true before any nodes are started:

   rosparam set use_sim_time true　　（运行ｒｏｓbag数据就是ｔｒｕｅ,实际数据就是false)

3. Bring up slam_gmapping, which will take in laser scans (in this case, on the base_scan topic) and produce a map:

   rosrun gmapping slam_gmapping scan:=scan     (我们前面bag.write写入的就是ｓｃａｎ)

   这里，也可以把ｏｄｏｍ里程计数据也加进去,就需要这么写

4. rosrun gmapping slam_gmapping scan:=scan  _odom_frame:=odom   (我们前面bag.write写入的就是ｓｃａｎ)

5.  

6. In a new terminal, start playing back the bag file to feed data to slam_gmapping:

   rosbag play --clock 

   • Wait for rosbag to finish and exit.

7. Save your new map to disk using map_saver from the map_server package:

   rosrun map_server map_saver -f 

遇到的一些问题

０．　ros 编译 Python 文件

https://blog.csdn.net/light_jiang2016/article/details/55505627

１．　问题与解决

No handlers could be found for logger rosout

 解决方法：

在转换文件（.py）的开头加上：

import logging
logging.basicConfig()

 

其他参考资料

参考网站：http://wiki.ros.org/slam_gmapping/Tutorials/MappingFromLoggedData 

https://stackoverflow.com/questions/53642503/how-to-convert-csv-to-rosbag

https://gaoyichao.com/Xiaotu/?book=turtlebot&title=gmapping%E7%9A%84ROS%E5%B0%81%E8%A3%85　　GMapping的ROS封装——初始化

 rosnode info /slam_gmapping 
----------------------------------------------------
Node [/slam_gmapping]
Publications: 
 * /map_metadata [nav_msgs/MapMetaData]
 * /tf [tf2_msgs/TFMessage]
 * /map [nav_msgs/OccupancyGrid]
 * /rosout [rosgraph_msgs/Log]
 * /slam_gmapping/entropy [std_msgs/Float64]

Subscriptions: 
 * /tf [tf2_msgs/TFMessage]
 * /scan [sensor_msgs/LaserScan]
 * /tf_static [tf2_msgs/TFMessage]
 * /clock [rosgraph_msgs/Clock]

Services: 
 * /slam_gmapping/set_logger_level
 * /slam_gmapping/get_loggers
 * /dynamic_ma