ROS2机器人实验报告提示03➡迷雾⬅

今天药忘吃喽~ 2022-09-15 15:58 137阅读 0赞

机器人必然会有传感器、调试工具如果用图形化则比命令行更容易使用，本节主要围绕可视化，拨开枯燥的数字迷雾，并将其形象的展示出来。

1.  rqt
2.  rviz2

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![watermark_type_ZHJvaWRzYW5zZmFsbGJhY2s_shadow_50_text_Q1NETiBAemhhbmdyZWxheQ_size_20_color_FFFFFF_t_70_g_se_x_16][]

文档中的内容，都有对应源码，参考如下文件夹：

![watermark_type_ZHJvaWRzYW5zZmFsbGJhY2s_shadow_50_text_Q1NETiBAemhhbmdyZWxheQ_size_20_color_FFFFFF_t_70_g_se_x_16 1][]

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本节使用案例三维点云，扩展案例为摄像头数据。输入如下命令：

*  source install/setup.bash
 *  ros2 run examples\_rclpy\_pointcloud\_publisher pointcloud\_publisher
 *  rviz2
 *  rqt
 *  ros2 topic echo /test\_cloud

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![watermark_type_ZHJvaWRzYW5zZmFsbGJhY2s_shadow_50_text_Q1NETiBAemhhbmdyZWxheQ_size_20_color_FFFFFF_t_70_g_se_x_16 2][]

以其中两组完整数据展示：

非常枯燥并且不知道是啥？？？

header:
      stamp:
        sec: 1634160052
        nanosec: 358446349
      frame_id: map
    height: 1
    width: 10000
    fields:
    - name: x
      offset: 0
      datatype: 7
      count: 1
    - name: y
      offset: 4
      datatype: 7
      count: 1
    - name: z
      offset: 8
      datatype: 7
      count: 1
    - name: intensity
      offset: 12
      datatype: 7
      count: 1
    is_bigendian: false
    point_step: 16
    row_step: 160000
    data:
    - 0
    - 0
    - 0
    - 192
    - 0
    - 0
    - 0
    - 192
    - 20
    - 103
    - 146
    - 190
    - 20
    - 103
    - 146
    - 190
    - 10
    - 212
    - 250
    - 191
    - 0
    - 0
    - 0
    - 192
    - 153
    - 174
    - 135
    - 190
    - 153
    - 174
    - 135
    - 190
    - 21
    - 168
    - 245
    - 191
    - 0
    - 0
    - 0
    - 192
    - 220
    - 38
    - 120
    - 190
    - 220
    - 38
    - 120
    - 190
    - 31
    - 124
    - 240
    - 191
    - 0
    - 0
    - 0
    - 192
    - 234
    - 81
    - 95
    - 190
    - 234
    - 81
    - 95
    - 190
    - 41
    - 80
    - 235
    - 191
    - 0
    - 0
    - 0
    - 192
    - 220
    - 7
    - 69
    - 190
    - 220
    - 7
    - 69
    - 190
    - 52
    - 36
    - 230
    - 191
    - 0
    - 0
    - 0
    - 192
    - 157
    - 116
    - 41
    - 190
    - 157
    - 116
    - 41
    - 190
    - 62
    - 248
    - 224
    - 191
    - 0
    - 0
    - 0
    - 192
    - 64
    - 198
    - 12
    - 190
    - 64
    - 198
    - 12
    - 190
    - 72
    - 204
    - 219
    - 191
    - 0
    - 0
    - 0
    - 192
    - 95
    - 89
    - 222
    - 189
    - 95
    - 89
    - 222
    - 189
    - '...'
    is_dense: false
    ---
    header:
      stamp:
        sec: 1634160052
        nanosec: 418641040
      frame_id: map
    height: 1
    width: 10000
    fields:
    - name: x
      offset: 0
      datatype: 7
      count: 1
    - name: y
      offset: 4
      datatype: 7
      count: 1
    - name: z
      offset: 8
      datatype: 7
      count: 1
    - name: intensity
      offset: 12
      datatype: 7
      count: 1
    is_bigendian: false
    point_step: 16
    row_step: 160000
    data:
    - 0
    - 0
    - 0
    - 192
    - 0
    - 0
    - 0
    - 192
    - 232
    - 86
    - 158
    - 190
    - 232
    - 86
    - 158
    - 190
    - 10
    - 212
    - 250
    - 191
    - 0
    - 0
    - 0
    - 192
    - 149
    - 207
    - 148
    - 190
    - 149
    - 207
    - 148
    - 190
    - 21
    - 168
    - 245
    - 191
    - 0
    - 0
    - 0
    - 192
    - 162
    - 79
    - 138
    - 190
    - 162
    - 79
    - 138
    - 190
    - 31
    - 124
    - 240
    - 191
    - 0
    - 0
    - 0
    - 192
    - 51
    - 209
    - 125
    - 190
    - 51
    - 209
    - 125
    - 190
    - 41
    - 80
    - 235
    - 191
    - 0
    - 0
    - 0
    - 192
    - 17
    - 91
    - 101
    - 190
    - 17
    - 91
    - 101
    - 190
    - 52
    - 36
    - 230
    - 191
    - 0
    - 0
    - 0
    - 192
    - 188
    - 101
    - 75
    - 190
    - 188
    - 101
    - 75
    - 190
    - 62
    - 248
    - 224
    - 191
    - 0
    - 0
    - 0
    - 192
    - 147
    - 28
    - 48
    - 190
    - 147
    - 28
    - 48
    - 190
    - 72
    - 204
    - 219
    - 191
    - 0
    - 0
    - 0
    - 192
    - 45
    - 173
    - 19
    - 190
    - 45
    - 173
    - 19
    - 190
    - '...'
    is_dense: false
    ---

--------------------

rviz2可视化效果如下：

![watermark_type_ZHJvaWRzYW5zZmFsbGJhY2s_shadow_50_text_Q1NETiBAemhhbmdyZWxheQ_size_20_color_FFFFFF_t_70_g_se_x_16 3][]

关于此部分全部内容参考：

[**点云发布（pointcloud\_publisher）之ROS2案例**][pointcloud_publisher_ROS2]

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数据之美由此可见。

节点图：

![watermark_type_ZHJvaWRzYW5zZmFsbGJhY2s_shadow_50_text_Q1NETiBAemhhbmdyZWxheQ_size_20_color_FFFFFF_t_70_g_se_x_16 4][]

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turtlesim画曲线：

*  ros2 run turtlesim turtlesim\_node

发布速度：

![watermark_type_ZHJvaWRzYW5zZmFsbGJhY2s_shadow_50_text_Q1NETiBAemhhbmdyZWxheQ_size_20_color_FFFFFF_t_70_g_se_x_16 5][]

对比速度和位姿数据差异性。

![watermark_type_ZHJvaWRzYW5zZmFsbGJhY2s_shadow_50_text_Q1NETiBAemhhbmdyZWxheQ_size_20_color_FFFFFF_t_70_g_se_x_16 6][]

--------------------

发布频率：

zhangrelay@cslg:~/code/ros2_ws$ ros2 topic echo /turtle1/cmd_vel 
    linear:
      x: 0.6
      y: 0.0
      z: 0.0
    angular:
      x: 0.0
      y: 0.0
      z: 0.3
    ---
    linear:
      x: 0.6
      y: 0.0
      z: 0.0
    angular:
      x: 0.0
      y: 0.0
      z: 0.3
    ---
    zhangrelay@cslg:~/code/ros2_ws$ ros2 topic echo /turtle1/pose
    x: 3.555169105529785
    y: 7.3056793212890625
    theta: -1.4535272121429443
    linear_velocity: 0.6000000238418579
    angular_velocity: 0.30000001192092896
    ---
    x: 3.55633807182312
    y: 7.2961506843566895
    theta: -1.4487272500991821
    linear_velocity: 0.6000000238418579
    angular_velocity: 0.30000001192092896
    ---

--------------------

更多二维曲线绘制，参考：

[**plotjuggler⬅ROS1/ROS2画轨迹神器➡rqt\_plot+rqt\_multiplot之超级加强版**][plotjuggler_ROS1_ROS2_rqt_plot_rqt_multiplot]

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请阅读并尽量完成镜像中如下部分：

![watermark_type_ZHJvaWRzYW5zZmFsbGJhY2s_shadow_50_text_Q1NETiBAemhhbmdyZWxheQ_size_20_color_FFFFFF_t_70_g_se_x_16 7][]

--------------------

ROS2基础部分到此结束。

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[watermark_type_ZHJvaWRzYW5zZmFsbGJhY2s_shadow_50_text_Q1NETiBAemhhbmdyZWxheQ_size_20_color_FFFFFF_t_70_g_se_x_16]: /images/20220828/4a7915385b9148fcb15d97560b4c5f3c.png
[watermark_type_ZHJvaWRzYW5zZmFsbGJhY2s_shadow_50_text_Q1NETiBAemhhbmdyZWxheQ_size_20_color_FFFFFF_t_70_g_se_x_16 1]: /images/20220828/dc4292627373495ea9e7186fc27710cf.png
[watermark_type_ZHJvaWRzYW5zZmFsbGJhY2s_shadow_50_text_Q1NETiBAemhhbmdyZWxheQ_size_20_color_FFFFFF_t_70_g_se_x_16 2]: /images/20220828/11afae88970f46bdafea9d2810685eb5.png
[watermark_type_ZHJvaWRzYW5zZmFsbGJhY2s_shadow_50_text_Q1NETiBAemhhbmdyZWxheQ_size_20_color_FFFFFF_t_70_g_se_x_16 3]: /images/20220828/891e2db6d13c4aae9667a758b9d73a2f.png
[pointcloud_publisher_ROS2]: https://blog.csdn.net/ZhangRelay/article/details/120641613?spm=1001.2014.3001.5501
[watermark_type_ZHJvaWRzYW5zZmFsbGJhY2s_shadow_50_text_Q1NETiBAemhhbmdyZWxheQ_size_20_color_FFFFFF_t_70_g_se_x_16 4]: /images/20220828/17186a0772f04f5fab6fa09376905988.png
[watermark_type_ZHJvaWRzYW5zZmFsbGJhY2s_shadow_50_text_Q1NETiBAemhhbmdyZWxheQ_size_20_color_FFFFFF_t_70_g_se_x_16 5]: /images/20220828/4d596795c9a946c4afc67bf9670185d4.png
[watermark_type_ZHJvaWRzYW5zZmFsbGJhY2s_shadow_50_text_Q1NETiBAemhhbmdyZWxheQ_size_20_color_FFFFFF_t_70_g_se_x_16 6]: /images/20220828/d3917423e60f4be6a9dbe145c25bf1d8.png
[plotjuggler_ROS1_ROS2_rqt_plot_rqt_multiplot]: https://blog.csdn.net/ZhangRelay/article/details/120598986?spm=1001.2014.3001.5501
[watermark_type_ZHJvaWRzYW5zZmFsbGJhY2s_shadow_50_text_Q1NETiBAemhhbmdyZWxheQ_size_20_color_FFFFFF_t_70_g_se_x_16 7]: /images/20220828/7a4a9b9229a84da2b0172d02b219f930.png