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可以建立联接,但micro-ROS init failed反复重启

jimmyx@jimmytse-PC:~/town_ws/chapt9/fishbot_ws$ ros2 run micro_ros_agent micro_ros_agent udp4 --port 8888
[1745073745.029776] info | UDPv4AgentLinux.cpp | init | running... | port: 8888
[1745073745.030124] info | Root.cpp | set_verbose_level | logger setup | verbose_level: 4
[1745073745.476669] info | Root.cpp | create_client | create | client_key: 0x2865ED34, session_id: 0x81
[1745073745.477005] info | SessionManager.hpp | establish_session | session established | client_key: 0x2865ED34, address: 192.168.113.101:47138
[1745073745.505339] info | ProxyClient.cpp | create_participant | participant created | client_key: 0x2865ED34, participant_id: 0x000(1)
[1745073749.534511] info | Root.cpp | delete_client | delete | client_key: 0x2865ED34
[1745073749.534573] info | SessionManager.hpp | destroy_session | session closed | client_key: 0x2865ED34, address: 192.168.113.101:47138
[1745073749.534600] info | Root.cpp | create_client | create | client_key: 0x5F96460F, session_id: 0x81
[1745073749.534607] info | SessionManager.hpp | establish_session | session established | client_key: 0x5F96460F, address: 192.168.113.101:47138
[1745073749.544918] info | ProxyClient.cpp | create_participant | participant created | client_key: 0x5F96460F, participant_id: 0x000(1)
^C[ros2run]: Interrupt

ESP32 串口接收到信息如下： code block

rst:0xc (SW_CPU_RESET),boot:0x13 (SPI_FAST_FLASH_BOOT)
configsip: 0, SPIWP:0xee
clk_drv:0x00,q_drv:0x00,d_drv:0x00,cs0_drv:0x00,hd_drv:0x00,wp_drv:0x00
mode:DIO, clock div:1
load:0x3fff0030,len:1184
load:0x40078000,len:13260
load:0x40080400,len:3028
entry 0x400805e4
OUT:left_speed=0.000000,right_speed=0.000000
micro-ROS init failed
ets Jul 29 2019 12:21:46

rst:0xc (SW_CPU_RESET),boot:0x13 (SPI_FAST_FLASH_BOOT)
configsip: 0, SPIWP:0xee
clk_drv:0x00,q_drv:0x00,d_drv:0x00,cs0_drv:0x00,hd_drv:0x00,wp_drv:0x00
mode:DIO, clock div:1
load:0x3fff0030,len:1184
load:0x40078000,len:13260
load:0x40080400,len:3028
entry 0x400805e4
OUT:left_speed=0.000000,right_speed=0.000000

ROS 2相关问题
1

fishbot上有IMU模块，但是第九章最后的小车代码没有IMU部分，想知道这部分代码如何编写。

FishBot二驱机器人
C

frames.png
路径规划报错：[component_container_isolated-1] [ERROR] [1745042787.273346658] [tf_help]: Transform data too old when converting from map to odom
[component_container_isolated-1] [ERROR] [1745042787.273400807] [tf_help]: Data time: 1745042787s 246927386ns, Transform time: 270s 532000000ns
rqt显示静态TF有大问题，同时
使用ros2 run tf2_ros tf2_echo base_link B_caster_link
显示
At time 0.0

Translation: [-0.300, 0.000, -0.147] Rotation: in Quaternion [0.000, 0.000, 0.000, 1.000] Rotation: in RPY (radian) [0.000, -0.000, 0.000] Rotation: in RPY (degree) [0.000, -0.000, 0.000] Matrix:
1.000 0.000 0.000 -0.300
0.000 1.000 0.000 0.000
0.000 0.000 1.000 -0.147
0.000 0.000 0.000 1.000
时间为0.0
该怎么处理？？卡住好几天了
ROS 2相关问题
A

9.0.6启动雷达服务前的配置工作：
（1）小车ip地址：192.168.123.193
（2）服务器ip地址：192.168.123.101(已经使用ifconfig检查，该虚拟机上查了一个网卡，网卡地址为192.168.123.101)
（3）服务器port：8889
（4）跳线帽连接无误，如图：a8b022ef-1ef8-49df-aad9-b65967b6d4bf-二驱小车雷达板.jpg
启动docker:
（1）xhost + && sudo docker run -it --rm -v /dev:/dev -v /dev/shm:/dev/shm --privileged -v /tmp/.X11-unix:/tmp/.X11-unix --device /dev/snd -e DISPLAY=unix$DISPLAY -p 8889:8888 registry.cn-hangzhou.aliyuncs.com/fishros/fishbot_laser
（2）输入2，显示如图：
039faafa-702b-4625-a8bd-c525b504498d-1744967742299.png
一直无雷达话题啊，雷达板内容显示如下：
173d5fdd-3f0a-48d3-8f86-d12697a5ad7d-启动服务后雷达板.jpg

FishBot二驱机器人
F

检测到程序发生异常退出，请打开：https://fishros.org.cn/forum 携带如下内容进行反馈

标题：使用一键安装过程中遇到程序崩溃

Traceback (most recent call last): File "/tmp/fishinstall/install.py", line 134, in <module> main() File "/tmp/fishinstall/install.py", line 123, in main run_tool_file(tools[code]['tool'].replace("/",".")) File "/tmp/fishinstall/tools/base.py", line 1473, in run_tool_file tool = importlib.import_module(file.replace(".py","")).Tool() AttributeError: module 'tools.tool_config_system_source' has no attribute 'Tool'

本次运行详细日志文件已保存至 /tmp/fishros_install.log

一键安装
P

做了几个控制插件对gazebo的模型进行控制然后进行仿真，但是发现好像插件识别不了gazebo的宏，打开gazebo的时候加载不出插件，请问有什么注意的点吗？以下是其中一个插件
#include "flapping_controller.hpp"
#include <gazebo/physics/Joint.hh>
#include <chrono>
#include <rclcpp/rclcpp.hpp>

using namespace gazebo;

FlappingController::FlappingController()
{
std::cout << "[FlappingController] Constructor called." << std::endl;
}

FlappingController::~FlappingController() {}

void FlappingController::Load(physics::ModelPtr model, sdf::ElementPtr sdf)
{
std::cout << "[FlappingController] Load() start." << std::endl;

if (!model)
{
std::cout << "[FlappingController] Model pointer is null!" << std::endl;
return;
}

this->model_ = model;
this->start_time_ = model->GetWorld()->SimTime().Double();
this->last_time_ = this->start_time_;

if (sdf->HasElement("namespace_model"))
this->ns_ = sdf->Getstd::string("namespace_model");
else
this->ns_ = "bird2";

try
{
this->ros_node_ = rclcpp::Node::make_shared(this->ns_ + "_flap_node");
}
catch (const std::exception &e)
{
std::cout << "[FlappingController] Failed to create ROS2 node: " << e.what() << std::endl;
return;
}

RCLCPP_INFO(this->ros_node_->get_logger(), "Creating subscriptions and publishers...");

this->flap_freq_sub_ = this->ros_node_->create_subscription<std_msgs::msg::Float32>(
"/" + ns_ + "/frequency", 10,
std::bind(&FlappingController::OnFlapFreqMsg, this, std::placeholders::_1));

this->height_sub_ = this->ros_node_->create_subscription<std_msgs::msg::Float32>(
"/" + ns_ + "/height", 10,
std::bind(&FlappingController::OnHeightMsg, this, std::placeholders::_1));

this->speed_pub_ = this->ros_node_->create_publisher<std_msgs::msg::Float32>(
"/" + ns_ + "/speed", 10);

this->update_connection_ = event::Events::ConnectWorldUpdateBegin(
std::bind(&FlappingController::OnUpdate, this));

RCLCPP_INFO(this->ros_node_->get_logger(), "FlappingController loaded.");
}

void FlappingController::OnFlapFreqMsg(const std_msgs::msg::Float32::SharedPtr msg)
{
this->SetFlappingFrequency(msg->data);
}

void FlappingController::SetFlappingFrequency(double freq)
{
this->flapping_freq_ = freq;
}

void FlappingController::OnHeightMsg(const std_msgs::msg::Float32::SharedPtr msg)
{
if (msg->data < 0.1)
this->flap_enabled_ = false;
else
this->flap_enabled_ = true;
}

void FlappingController::OnUpdate()
{
if (!this->model_)
return;

double now = model_->GetWorld()->SimTime().Double();
if (!flap_enabled_)
return;

double elapsed = now - this->start_time_;
double left = flapping_amp_ * sin(2 * M_PI * flapping_freq_ * elapsed);
double right = -left;

auto joint_left = model_->GetJoint("joint_4");
auto joint_right = model_->GetJoint("joint_6");

if (!joint_left || !joint_right)
{
std::cerr << "[FlappingController] Failed to find joint_4 or joint_6!" << std::endl;
return;
}

joint_left->SetPosition(0, left);
joint_right->SetPosition(0, right);

std_msgs::msg::Float32 speed_msg;
speed_msg.data = left;
this->speed_pub_->publish(speed_msg);
}

GZ_REGISTER_MODEL_PLUGIN(FlappingController)

动手学ROS2
D

c82dfc33-7b9f-43b9-a80e-78f7ffad0b42-image.png
启动roscore之后输入rviz，无法启动。报错。
系统为ubuntu20.04，ros1 noetic，显卡为4090D,使用独立显卡。已经使用X11显示模式。显卡驱动570，驱动已经是最推荐的。cuda11.8。重新安装rviz也没用。glxinfo | grep "OpenGL version" 可以正确显示显卡。

'OgreWindow(1)' already exists in GLRenderSystem::_createRenderWindow at /build/ogre-1.9-kiU5_5/ogre-1.9-1.9.0+dfsg1/RenderSystems/GL/src/OgreGLRenderSystem.cpp (line 1054)
rviz::RenderSystem: error creating render window: OGRE EXCEPTION(2:InvalidParametersException): Window with name 'OgreWindow(1)' already exists in GLRenderSystem::_createRenderWindow at /build/ogre-1.9-kiU5_5/ogre-1.9-1.9.0+dfsg1/RenderSystems/GL/src/OgreGLRenderSystem.cpp (line 1054)
[ERROR] [1744897217.932311762]: Unable to create the rendering window after 100 tries.

综合问题
3

鱼总，四驱板的原理图没有防反接电路和和连接上位机的串口电路吗？

FishBot四驱机器人V2
L

ros2 humble和gazebo 11为什么使用gazebo加载机器人模型和世界没有/gazebo/ "model_states" 话题发布
输入ros2 topic echo /gazebo/model_states显示错误
WARNING: topic [/gazebo/model_states] does not appear to be published yet
Could not determine the type for the passed topic
怎么解决，谢谢

ROS2机器人开发：从入门到实践
J

如题，还想问问摄像头能够在通过wifi，把视频保存在电脑上吗？我想采集小车前后左右四个角度的视频

FishBot二驱机器人
R

1：大家有没有复杂一些的工业级机器人源码可以分享？比如玻璃清洁机器人，泳池清洁机器人，或者较复杂的机械臂、视觉识别、空间定位之类的
2：感觉仅仅依赖社区的框架，很难做出复杂的或解决特定问题的机器人，但是自己做缺乏方向，有没有各个方向深入一些的路线或学习资料

综合问题
R

环境是wsl fishbot gazebo模拟
参考官方文档https://docs.nav2.org/tutorials/docs/navigation2_with_stvl.html和git仓库里的配置文件，配置以后没有任何效果，无法避开低于雷达高度的障碍物，在local_costmap中也没有现实障碍物，有人成功配置过或有参考配置吗
尝试了多个配置方案，在global_costmap中也配置过

local_costmap: local_costmap: ros__parameters: update_frequency: 5.0 publish_frequency: 2.0 global_frame: odom robot_base_frame: base_link use_sim_time: True rolling_window: true width: 3 height: 3 resolution: 0.05 robot_radius: 0.12 # plugins: ["voxel_layer", "stvl_layer","inflation_layer"] plugins: ["stvl_layer","inflation_layer"] stvl_layer: plugin: "spatio_temporal_voxel_layer/SpatioTemporalVoxelLayer" enabled: true voxel_decay: 15.0 # seconds if linear, e^n if exponential decay_model: 0 # 0=linear, 1=exponential, -1=persistent voxel_size: 0.02 # meters track_unknown_space: true # default space is known mark_threshold: 0 # voxel height update_footprint_enabled: true combination_method: 1 # 1=max, 0=override origin_z: 0.0 # meters publish_voxel_map: false # default off transform_tolerance: 0.5 # seconds mapping_mode: false # default off, saves map not for navigation map_save_duration: 60.0 # default 60s, how often to autosave observation_sources: rgbd1_mark rgbd1_clear rgbd1_mark: data_type: PointCloud2 topic: /camera_sensor/points marking: true clearing: false obstacle_range: 3.0 # meters min_obstacle_height: 0.1 # default 0, meters max_obstacle_height: 2.0 # default 3, meters expected_update_rate: 0.0 # default 0, if not updating at this rate at least, remove from buffer observation_persistence: 0.0 # default 0, use all measurements taken during now-value, 0=latest inf_is_valid: false # default false, for laser scans filter: "passthrough" # default passthrough, apply "voxel", "passthrough", or no filter to sensor data, recommend on voxel_min_points: 0 # default 0, minimum points per voxel for voxel filter clear_after_reading: true # default false, clear the buffer after the layer gets readings from it rgbd1_clear: data_type: PointCloud2 topic: /camera_sensor/points marking: false clearing: true max_z: 7.0 # default 0, meters min_z: 0.1 # default 10, meters vertical_fov_angle: 0.8745 # default 0.7, radians horizontal_fov_angle: 1.048 # default 1.04, radians decay_acceleration: 5.0 # default 0, 1/s^2. If laser scanner MUST be 0 model_type: 0 inflation_layer: plugin: "nav2_costmap_2d::InflationLayer" cost_scaling_factor: 3.0 inflation_radius: 0.55 # voxel_layer: # plugin: "nav2_costmap_2d::VoxelLayer" # enabled: True # publish_voxel_map: True # origin_z: 0.0 # z_resolution: 0.05 # z_voxels: 16 # max_obstacle_height: 2.0 # mark_threshold: 0 # observation_sources: scan # scan: # topic: /scan # max_obstacle_height: 2.0 # clearing: True # marking: True # data_type: "LaserScan" # raytrace_max_range: 3.0 # raytrace_min_range: 0.0 # obstacle_max_range: 2.5 # obstacle_min_range: 0.0 # static_layer: # plugin: "nav2_costmap_2d::StaticLayer" # map_subscribe_transient_local: True always_send_full_costmap: True ... other parameters ... local_costmap: local_costmap: ros__parameters: update_frequency: 5.0 publish_frequency: 2.0 global_frame: odom robot_base_frame: base_link # Ensure this matches your robot's TF use_sim_time: True rolling_window: true width: 3 height: 3 resolution: 0.05 robot_radius: 0.12 # Or use footprint parameter transform_tolerance: 0.5 # Increased tolerance can help with timing issues # List both layers here, plus inflation plugins: ["scan_voxel_layer", "inflation_layer"] # Configuration for the standard VoxelLayer (using LaserScan) scan_voxel_layer: plugin: "nav2_costmap_2d::VoxelLayer" enabled: True publish_voxel_map: True # Publishes to /local_costmap/scan_voxel_layer/voxel_grid (namespaced) origin_z: 0.0 z_resolution: 0.05 z_voxels: 16 max_obstacle_height: 2.0 mark_threshold: 0 combination_method: 1 # 1=max observation_sources: scan # Source name for this layer scan: # Configuration for the 'scan' source topic: /scan max_obstacle_height: 2.0 clearing: True marking: True data_type: "LaserScan" raytrace_max_range: 3.0 obstacle_max_range: 2.5 # Configuration for the Spatio-Temporal Voxel Layer (using PointCloud2) # stvl_layer: # plugin: "spatio_temporal_voxel_layer/SpatioTemporalVoxelLayer" # enabled: true # publish_voxel_map: true # Publishes to /local_costmap/stvl_layer/voxel_map (namespaced) # voxel_decay: 10.0 # Shorter decay for local map # decay_model: 0 # 0=linear # voxel_size: 0.05 # Match resolution if desired # track_unknown_space: true # mark_threshold: 0 # update_footprint_enabled: true # combination_method: 1 # 1=max # origin_z: 0.0 # transform_tolerance: 0.5 # Increased tolerance # mapping_mode: false # observation_sources: pointcloud # Source name for this layer # pointcloud: # Configuration for the 'pointcloud' source # data_type: PointCloud2 # topic: /camera_sensor/points # marking: true # clearing: true # STVL can often use a single source for marking/clearing PointCloud2 # obstacle_range: 3.0 # min_obstacle_height: 0.05 # Catch low obstacles # max_obstacle_height: 2.0 # expected_update_rate: 0.0 # observation_persistence: 0.0 # inf_is_valid: false # filter: "passthrough" # voxel_min_points: 1 # # Consider adding separate mark/clear sources if clearing isn't effective # Configuration for the InflationLayer (runs last) inflation_layer: plugin: "nav2_costmap_2d::InflationLayer" cost_scaling_factor: 3.0 inflation_radius: 0.55 # Adjust based on robot size and environment always_send_full_costmap: True # Useful for debugging

local_costmap:
local_costmap:
ros__parameters:
use_sim_time: True
update_frequency: 5.0
publish_frequency: 2.0
global_frame: odom
robot_base_frame: base_link
rolling_window: true
width: 8
height: 8
resolution: 0.05
# footprint: "[ [0.254, 0.2159], [0.254, -0.2159], [-0.254, -0.2159], [-0.254, 0.2159] ]"
# footprint_padding: 0.1
robot_radius: 0.12
track_unknown_space: false
plugins: ["spatio_temporal_voxel_layer", "inflation_layer"]
inflation_layer:
plugin: "nav2_costmap_2d::InflationLayer"
cost_scaling_factor: 3.0
inflation_radius: 0.5
spatio_temporal_voxel_layer:
plugin: "spatio_temporal_voxel_layer/SpatioTemporalVoxelLayer"
enabled: true
voxel_decay: 15.
decay_model: 0
voxel_size: 0.05
track_unknown_space: true
unknown_threshold: 15
mark_threshold: 0
update_footprint_enabled: true
combination_method: 1
origin_z: 0.0
publish_voxel_map: false
transform_tolerance: 0.2
mapping_mode: false
map_save_duration: 60.0
observation_sources: depth_cam
# # lidar:
# data_type: PointCloud2
# topic: /sensors/lidar_0/segmented_points
# marking: true
# clearing: true
# obstacle_range: 8.0
# min_obstacle_height: 0.254
# max_obstacle_height: 0.8
# expected_update_rate: 0.0
# observation_persistence: 0.0
# inf_is_valid: false
# filter: "voxel"
# voxel_min_points: 0
# clear_after_reading: true
# max_z: 8.0
# min_z: 0.3
# vertical_fov_angle: 0.785398
# vertical_fov_padding: 0.05
# horizontal_fov_angle: 6.29
# decay_acceleration: 15.0
# model_type: 1
depth_cam:
data_type: PointCloud2
topic: /camera_sensor/points
marking: true
clearing: true
obstacle_range: 2.0
min_obstacle_height: 0.1524
max_obstacle_height: 0.8
expected_update_rate: 0.0
observation_persistence: 0.0
inf_is_valid: false
filter: "voxel"
voxel_min_points: 0
clear_after_reading: true
max_z: 2.0
min_z: 0.2
vertical_fov_angle: 1.047
horizontal_fov_angle: 1.221
decay_acceleration: 15.0
model_type: 0
always_send_full_costmap: True

VIP问答专区
10309771531
colcon build之后没有生成可执行文件 背景：

学习ROS2中途安装了一个miniconda，然后就出现了各种各样环境兼容的问题。先是vscode打不开，后来发现用colcon build的时候生成不了可执行文件和接口库文件，安装miniconda之前的文件可以生成可执行文件，但是之后的就不行。

问题描述：

colcon build没办法正确生成可执行文件，没有报错，但就是会忽略掉在cmakelist里配置好的文件，需要手动生成。应该是因为中途安装了一个miniconda，配置了环境之后就坏掉了。我不会调，所以直接把miniconda卸载了。但还是没法正确编译。在同一个功能包里，有的可以正确编译生成可执行文件，有的不行。colcon build也可以正常运行，不报错。

具体细节和上下文：

可以看到没有报错，但是在同一个功能包chapt4_interfaces下的facedector在install/srv下生成了库文件，但是partol没有。cpp和python文件也是类似，可执行文件和库文件都没办法正确生成，就不截图了。
0da19b52-baaf-45cd-a344-4a2d3e739df8-图片.png
以下是chapt4_interfaces对应的cmakelist文件：

cmake_minimum_required(VERSION 3.8) project(chapt4_interfaces) if(CMAKE_COMPILER_IS_GNUCXX OR CMAKE_CXX_COMPILER_ID MATCHES "Clang") add_compile_options(-Wall -Wextra -Wpedantic) endif() # find dependencies find_package(ament_cmake REQUIRED) find_package(sensor_msgs REQUIRED) find_package(rosidl_default_generators REQUIRED) rosidl_generate_interfaces(${PROJECT_NAME} "srv/FaceDetector.srv" "srv/Partol.srv" DEPENDENCIES sensor_msgs ) if(BUILD_TESTING) find_package(ament_lint_auto REQUIRED) # the following line skips the linter which checks for copyrights # comment the line when a copyright and license is added to all source files set(ament_cmake_copyright_FOUND TRUE) # the following line skips cpplint (only works in a git repo) # comment the line when this package is in a git repo and when # a copyright and license is added to all source files set(ament_cmake_cpplint_FOUND TRUE) ament_lint_auto_find_test_dependencies() endif() ament_package()

以下是package.xml的内容

<?xml version="1.0"?> <?xml-model href="http://download.ros.org/schema/package_format3.xsd" schematypens="http://www.w3.org/2001/XMLSchema"?> <package format="3"> <name>chapt4_interfaces</name> <version>0.0.0</version> <description>TODO: Package description</description> <maintainer email="aroughwelcome@163.com">phoebe</maintainer> <license>Apache-2.0</license> <buildtool_depend>ament_cmake</buildtool_depend> <member_of_group>rosidl_interface_packages</member_of_group> <depend>sensor_msgs</depend> <depend>rosidl_default_generators</depend> <test_depend>ament_lint_auto</test_depend> <test_depend>ament_lint_common</test_depend> <export> <build_type>ament_cmake</build_type> </export> </package> 尝试过的解决方法：

现在已经把miniconda卸载了，vscode也重装了，ROS和环境也重新配置了一遍。但还是没法正确编译。

手动生成的话是可以正常生成可执行文件的。

【我不太了解，有什么需要补充或者可以尝试的，请大家告诉我。我会积极修改的，谢谢^ ^】

动手学ROS2
2

回复: [FishBot教程] 9.0.6. 雷达驱动及建图测试
![替代文字](屏幕截图 2025-04-15 175801.png 图片地址)

FishBot二驱机器人
liusiyu_alex_nuaaL
最近有个项目用的是宇树雷达L1进行3D建图，按照网上的教程打算用cartographer算法来搞，但是运行起来从rviz来看只有2维地图，点云和imu的数据都是有的 cartographer.launch.py import os from launch import LaunchDescription from launch.substitutions import LaunchConfiguration from launch_ros.actions import Node from launch_ros.substitutions import FindPackageShare def generate_launch_description(): # 定位到功能包的地址 pkg_share = FindPackageShare(package='robot_cartographer').find('robot_cartographer') #=====================运行节点需要的配置======================================================================= # 是否使用仿真时间 use_sim_time = LaunchConfiguration('use_sim_time', default='false') # 地图的分辨率 resolution = LaunchConfiguration('resolution', default='0.05') # 地图的发布周期 publish_period_sec = LaunchConfiguration('publish_period_sec', default='1.0') # 配置文件夹路径 configuration_directory = LaunchConfiguration('configuration_directory',default= os.path.join(pkg_share, 'config') ) # 配置文件 configuration_basename = LaunchConfiguration('configuration_basename', default='robot_3d.lua') rviz_config_dir = LaunchConfiguration('rviz_config_dir',default= os.path.join(pkg_share, 'rviz') ) #=====================声明三个节点，cartographer/occupancy_grid_node/rviz_node================================= cartographer_node = Node( package='cartographer_ros', executable='cartographer_node', name='cartographer_node', output='screen', parameters=[{'use_sim_time': use_sim_time}], arguments=['-configuration_directory', configuration_directory, '-configuration_basename', configuration_basename], remappings = [ ('points2', 'cloud')],) occupancy_grid_node = Node( package='cartographer_ros', executable='cartographer_occupancy_grid_node', name='occupancy_grid_node', output='screen', parameters=[{'use_sim_time': use_sim_time}], arguments=['-resolution', resolution, '-publish_period_sec', publish_period_sec]) rviz_node = Node( package='rviz2', executable='rviz2', name='rviz2', arguments=['-d', rviz_config_dir], parameters=[{'use_sim_time': use_sim_time}], output='screen') #===============================================定义启动文件======================================================== ld = LaunchDescription() ld.add_action(cartographer_node) ld.add_action(occupancy_grid_node) ld.add_action(rviz_node) return ld robot_3d.lua -- Copyright 2016 The Cartographer Authors -- -- Licensed under the Apache License, Version 2.0 (the "License"); -- you may not use this file except in compliance with the License. -- You may obtain a copy of the License at -- -- http://www.apache.org/licenses/LICENSE-2.0 -- -- Unless required by applicable law or agreed to in writing, software -- distributed under the License is distributed on an "AS IS" BASIS, -- WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -- See the License for the specific language governing permissions and -- limitations under the License. include "map_builder.lua" include "trajectory_builder.lua" options = { map_builder = MAP_BUILDER, trajectory_builder = TRAJECTORY_BUILDER, map_frame = "map", tracking_frame = "imu_link", published_frame = "base_link", odom_frame = "odom", provide_odom_frame = false, publish_frame_projected_to_2d = false, -- use_pose_extrapolator = true, use_odometry = false, use_nav_sat = false, use_landmarks = false, num_laser_scans = 0, num_multi_echo_laser_scans = 0, num_subdivisions_per_laser_scan = 1, num_point_clouds = 1, lookup_transform_timeout_sec = 0.2, submap_publish_period_sec = 0.3, pose_publish_period_sec = 5e-3, trajectory_publish_period_sec = 30e-3, rangefinder_sampling_ratio = 1., odometry_sampling_ratio = 1., fixed_frame_pose_sampling_ratio = 1., imu_sampling_ratio = 1., landmarks_sampling_ratio = 1., } TRAJECTORY_BUILDER_3D.num_accumulated_range_data = 160 MAP_BUILDER.use_trajectory_builder_3d = true MAP_BUILDER.num_background_threads = 7 POSE_GRAPH.optimization_problem.huber_scale = 5e2 POSE_GRAPH.optimize_every_n_nodes = 320 POSE_GRAPH.constraint_builder.sampling_ratio = 0.03 POSE_GRAPH.optimization_problem.ceres_solver_options.max_num_iterations = 10 POSE_GRAPH.constraint_builder.min_score = 0.62 POSE_GRAPH.constraint_builder.global_localization_min_score = 0.66 return options 机器人urdf文件 <robot name="cartographer_backpack_3d"> <material name="orange"> <color rgba="1.0 0.5 0.2 1" /> </material> <material name="gray"> <color rgba="0.2 0.2 0.2 1" /> </material> <!-- IMU or 底盘 （可以描述尺寸大小也可以不描述） --> <link name="base_link" /> <link name="imu_link" /> <joint name="imu_link_joint" type="fixed"> <parent link="base_link" /> <child link="imu_link" /> <origin xyz="0 0 0" rpy="0 0 0" /> </joint> <!-- 描述雷达的尺寸大小、颜色 --> <link name="laser_link"> <visual> <origin xyz="0.0 0.0 0.0" /> <geometry> <cylinder length="0.07" radius="0.05" /> </geometry> <material name="gray" /> </visual> </link> <!-- 描述 雷达和IMU/底盘 的相对位姿 --> <joint name="laser_link_joint" type="fixed"> <parent link="imu_link" /> <child link="laser_link" /> <origin xyz="0.007698 0.014655 -0.00667" rpy="0 0 0" /> </joint> </robot> 所有话题 robot@ubuntu:~$ ros2 topic list /clicked_point /cloud /constraint_list /goal_pose /initialpose /joint_states /landmark_poses_list /map /map_updates /parameter_events /robot_description /rosout /scan_matched_points2 /submap_list /tf /tf_static /trajectory_node_list

rqt的节点图
e3d4d21b-1c2e-4a68-ac88-4607657815bc-图片.png

rviz界面
3e2c7027-4cb1-4ad8-be6d-6c88626fd6cb-图片.png

动手学ROS2
1

在运行指令os2 launch slam_toolbox online_async_launch.py use_sim_time:=false
且雷达正常工作情况下报错，使用rviz也无法接收到地图数据
7055ca20-0a86-4f11-818f-9277362f590f-图片.png

FishBot二驱机器人
X

用一键安装ros2后，发现没有rqt_robot_steering包，sudo apt install ros-humble-rqt-robot-steering安装启动后，再启动ros2 run turtlesim turtlesim_node，在/cmd_vel前添加turtle1，发现控制不了小乌龟运动

综合问题
B

具体需要改动哪部分啊

综合问题
1

我启动官方的turtlebot3_simulations/turtlebot3_gazebo/launch/multi_robot.launch.py，官方的为3个turtlebot3同时启动，因为需要完成多机器人导航，我为了先测试修改为启动1个小车，这个小车都添加了命名空间TB3_1。
然后我将官方的turtlebot3_navigation2/launch/navigation2.launch.py中的这一部分也添加了命名空间
58f28cfa030e6d11bda1ffa35c64f0a8.jpg
aa1e7fcd1719ce868a722435febe6f52.jpg
最后我启动，但是rviz里面显示找不到map坐标系，点击2d pose estimate也无法设置初始位姿
23c1b5c64a503f297a4b611b08592e08.jpg
tf树里也没有map
frames1.png
我想问问是不是我这样的修改想法太简单了，已经困扰了我好多天了，我也试过修改burger.yaml里面的参数文件，同样也是没有效果，所以来求助各位！

综合问题
1

li@ubantu:~/chapt9/microros_ws$ ros2 launch bringup bringup.launch.py
[INFO] [launch]: All log files can be found below /home/li/.ros/log/2025-04-15-01-28-25-394866-ubantu-4599
[INFO] [launch]: Default logging verbosity is set to INFO
[INFO] [joint_state_publisher-1]: process started with pid [4601]
[INFO] [robot_state_publisher-2]: process started with pid [4603]
[INFO] [odom2tf-3]: process started with pid [4605]
[INFO] [micro_ros_agent-4]: process started with pid [4624]
[robot_state_publisher-2] [INFO] [1744651705.590238505] [robot_state_publisher]: got segment base_footprint
[robot_state_publisher-2] [INFO] [1744651705.590380034] [robot_state_publisher]: got segment base_link
[robot_state_publisher-2] [INFO] [1744651705.590393148] [robot_state_publisher]: got segment laser_link
[micro_ros_agent-4] [1744651706.006637] info | TermiosAgentLinux.cpp | init | running... | fd: 3
[micro_ros_agent-4] [1744651706.007247] info | Root.cpp | set_verbose_level | logger setup | verbose_level: 6
[joint_state_publisher-1] [INFO] [1744651706.257693092] [joint_state_publisher]: Waiting for robot_description to be published on the robot_description topic...
[INFO] [ydlidar_node-5]: process started with pid [4652]
[ydlidar_node-5] [INFO] [1744651711.305964413] [ydlidar_node]: [YDLIDAR INFO] Current ROS Driver Version: 1.0.1
[ydlidar_node-5]
[ydlidar_node-5] [2025-04-15 01:28:31][info] SDK initializing
[ydlidar_node-5] [2025-04-15 01:28:31][info] SDK has been initialized
[ydlidar_node-5] [2025-04-15 01:28:31][info] SDK Version: 1.2.9
[ydlidar_node-5] [2025-04-15 01:28:31][info] Connect elapsed time 10 ms
[ydlidar_node-5] [2025-04-15 01:28:31][info] Lidar successfully connected [/dev/ttyUSB1:115200]
[ydlidar_node-5] [2025-04-15 01:28:31][info] Lidar running correctly! The health status good
[ydlidar_node-5] [2025-04-15 01:28:31][info] Current Lidar Model Code 12
[ydlidar_node-5] [2025-04-15 01:28:31][info] Check status, Elapsed time 0 ms
[ydlidar_node-5] [2025-04-15 01:28:31][info] Lidar init success, Elapsed time [12]ms
[ydlidar_node-5] [2025-04-15 01:28:31][info] Start to getting intensity flag
[ydlidar_node-5] [2025-04-15 01:28:33][info] [YDLIDAR] End to getting intensity flag
[ydlidar_node-5] [2025-04-15 01:28:33][info] [YDLIDAR] Create thread 0x41800640
[ydlidar_node-5] [2025-04-15 01:28:33][info] Successed to start scan mode, Elapsed time 2537 ms
[ydlidar_node-5] [2025-04-15 01:28:34][error] Timeout count: 1
[ydlidar_node-5] [2025-04-15 01:28:35][error] Timeout count: 2
[ydlidar_node-5] [2025-04-15 01:28:36][error] Timeout count: 3
[ydlidar_node-5] [2025-04-15 01:28:38][error] Check Sum 0x202A != 0x6878
[ydlidar_node-5] [2025-04-15 01:28:39][error] Timeout count: 1
[ydlidar_node-5] [2025-04-15 01:28:40][error] Check Sum 0x6B1A != 0x7812
[ydlidar_node-5] [2025-04-15 01:28:40][error] Timeout count: 2
[ydlidar_node-5] [2025-04-15 01:28:41][error] Timeout count: 1
[ydlidar_node-5] [2025-04-15 01:28:42][error] Check Sum 0x5D90 != 0x02CD
[ydlidar_node-5] [2025-04-15 01:28:42][error] Timeout count: 2
[ydlidar_node-5] [2025-04-15 01:28:43][error] Timeout count: 3
[ydlidar_node-5] [2025-04-15 01:28:44][error] Failed to turn on the Lidar, because the lidar is [Device Failed].
[ydlidar_node-5] [INFO] [1744651724.497044306] [ydlidar_node]: [YDLIDAR INFO] Now YDLIDAR is stopping .......
[INFO] [ydlidar_node-5]: process has finished cleanly [pid 4652]
[ydlidar_node-5]

13316a64-d4fb-4b6a-baa7-1985c2d8a1dc-image.png
我改完后的launch.py如下：
import launch
import launch_ros
from ament_index_python.packages import get_package_share_directory
from launch.launch_description_sources import PythonLaunchDescriptionSource

def generate_launch_description():
bringup_dir = get_package_share_directory(
'bringup')
ydlidar_ros2_dir = get_package_share_directory(
'ydlidar')

urdf2tf = launch.actions.IncludeLaunchDescription( PythonLaunchDescriptionSource( [bringup_dir, '/launch', '/urdf2tf.launch.py']), ) odom2tf = launch_ros.actions.Node( package='bringup', executable='odom2tf', output='screen' ) microros_agent = launch_ros.actions.Node( package='micro_ros_agent', executable='micro_ros_agent', arguments=[ 'serial', # 切换为串口模式 '-b', '115200', # 波特率参数（需字符串类型） '--dev', '/dev/ttyUSB1', # 设备路径 '-v6' # 日志详细级别 ], output='screen' # 保持终端输出可见 ) ydlidar = launch.actions.IncludeLaunchDescription( PythonLaunchDescriptionSource( [ydlidar_ros2_dir, '/launch', '/ydlidar_launch.py']), ) # 使用 TimerAction 启动后 5 秒执行 ydlidar 节点 ydlidar_delay = launch.actions.TimerAction(period=5.0, actions=[ydlidar]) return launch.LaunchDescription([ urdf2tf, odom2tf, microros_agent, ydlidar_delay ])

不知道是什么原因，该怎么修改呢？
后面单独运行这个ros2 launch ydlidar ydlidar_launch.py显示如下（上一章节显示点云成功了的）
li@ubantu:~/chapt9/microros_ws$ ros2 launch ydlidar ydlidar_launch.py
[INFO] [launch]: All log files can be found below /home/li/.ros/log/2025-04-15-01-32-03-185276-ubantu-4693
[INFO] [launch]: Default logging verbosity is set to INFO
[INFO] [ydlidar_node-1]: process started with pid [4704]
[ydlidar_node-1] [INFO] [1744651923.991974545] [ydlidar_node]: [YDLIDAR INFO] Current ROS Driver Version: 1.0.1
[ydlidar_node-1]
[ydlidar_node-1] [2025-04-15 01:32:03][info] SDK initializing
[ydlidar_node-1] [2025-04-15 01:32:03][info] SDK has been initialized
[ydlidar_node-1] [2025-04-15 01:32:03][info] SDK Version: 1.2.9
[ydlidar_node-1] [2025-04-15 01:32:03][info] Connect elapsed time 6 ms
[ydlidar_node-1] [2025-04-15 01:32:03][info] Lidar successfully connected [/dev/ttyUSB1:115200]
[ydlidar_node-1] [2025-04-15 01:32:03][info] Lidar running correctly! The health status good
[ydlidar_node-1] [2025-04-15 01:32:03][info] Current Lidar Model Code 12
[ydlidar_node-1] [2025-04-15 01:32:03][info] Check status, Elapsed time 1 ms
[ydlidar_node-1] [2025-04-15 01:32:04][info] Lidar init success, Elapsed time [8]ms
[ydlidar_node-1] [2025-04-15 01:32:04][info] Start to getting intensity flag
[ydlidar_node-1] [2025-04-15 01:32:05][info] [YDLIDAR] End to getting intensity flag
[ydlidar_node-1] [2025-04-15 01:32:05][info] [YDLIDAR] Create thread 0xB9400640
[ydlidar_node-1] [2025-04-15 01:32:05][error] Check Sum 0xFA01 != 0x0520
[ydlidar_node-1] [2025-04-15 01:32:06][info] Successed to start scan mode, Elapsed time 2073 ms
[ydlidar_node-1] [2025-04-15 01:32:06][error] Timeout count: 1
[ydlidar_node-1] [2025-04-15 01:32:07][error] Timeout count: 2
[ydlidar_node-1] [2025-04-15 01:32:08][error] Timeout count: 3
[ydlidar_node-1] [2025-04-15 01:32:11][error] Timeout count: 1
[ydlidar_node-1] [2025-04-15 01:32:12][error] Timeout count: 2
[ydlidar_node-1] [2025-04-15 01:32:13][error] Timeout count: 3
[ydlidar_node-1] [2025-04-15 01:32:15][error] Timeout count: 1
[ydlidar_node-1] [2025-04-15 01:32:16][error] Failed to turn on the Lidar, because the lidar is [Device Failed].
[ydlidar_node-1] [INFO] [1744651936.529456617] [ydlidar_node]: [YDLIDAR INFO] Now YDLIDAR is stopping .......
[INFO] [ydlidar_node-1]: process has finished cleanly [pid 4704]
[ydlidar_node-1]

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  • 社区运营&开源工具

    学习资源 社区运营 一键安装 FishROS2GO
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  • 408
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    法

    @小鱼 鱼哥显示屏上总是显示ping timeout什么原因啊

  • 针对社区VIP用户问答专区

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    1

    @小鱼 鱼哥·，我就是串口驱动雷达的，我wifi不行，但是无法建图就不知道是什么原因了，我是有点云数据的，可以在rviz2里面显示出来

  • 《ROS2机器人开发：从入门到实践》书籍配套资料答疑专区

    ROS 2相关问题
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    C

    解决了，不是tf的问题，是代码的问题

  • 综合问题讨论版块 | 版主 @吴凯荣 @小鱼

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    D

    c82dfc33-7b9f-43b9-a80e-78f7ffad0b42-image.png
    启动roscore之后输入rviz，无法启动。报错。
    系统为ubuntu20.04，ros1 noetic，显卡为4090D,使用独立显卡。已经使用X11显示模式。显卡驱动570，驱动已经是最推荐的。cuda11.8。重新安装rviz也没用。glxinfo | grep "OpenGL version" 可以正确显示显卡。

    'OgreWindow(1)' already exists in GLRenderSystem::_createRenderWindow at /build/ogre-1.9-kiU5_5/ogre-1.9-1.9.0+dfsg1/RenderSystems/GL/src/OgreGLRenderSystem.cpp (line 1054)
    rviz::RenderSystem: error creating render window: OGRE EXCEPTION(2:InvalidParametersException): Window with name 'OgreWindow(1)' already exists in GLRenderSystem::_createRenderWindow at /build/ogre-1.9-kiU5_5/ogre-1.9-1.9.0+dfsg1/RenderSystems/GL/src/OgreGLRenderSystem.cpp (line 1054)
    [ERROR] [1744897217.932311762]: Unable to create the rendering window after 100 tries.

  • 机械臂力控板块 | 版主： @陆门马

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    小伊小

    你的文章很好地概述了在轻擎2机械臂上实现基于雅可比矩阵的末端力控（导纳控制的一种简化形式）的过程。这种方法结合了位置控制和力控制，使得机械臂在某些轴上能够施加期望的力，而在其他轴上则继续跟踪期望的位置轨迹。以下是对你文章的一些补充和澄清，以及对潜在读者的进一步解释：

    1. 雅可比矩阵的作用

    雅可比矩阵（Jacobian Matrix）在机器人学中非常重要，因为它描述了机器人关节空间速度到末端执行器空间速度的线性映射。在力控中，雅可比矩阵的转置被用来将末端执行器空间的力映射到关节空间的力矩。这种映射是实现力控的关键步骤之一。

    2. 力位混控

    力位混控（Hybrid Force/Position Control）允许机器人在同一时间对不同的自由度进行不同的控制。在你的例子中，机械臂在特定轴上施加力，同时在其他轴上跟踪位置轨迹。这种控制策略对于需要与环境进行交互的机器人任务非常有用。

    3. 实时性

    由于你的控制算法依赖于实时数据（如当前末端位置和速度），因此确保系统的实时性至关重要。这意味着从传感器读取数据、计算控制输入以及将控制信号发送到电机都需要在非常短的时间内完成。

    4. 摩擦力补偿

    摩擦力是机器人系统中常见的非线性干扰因素。在你的代码中，你通过检查关节速度并对非常小的速度应用一个小的力来尝试补偿摩擦力。这种方法虽然简单，但在某些情况下可能有效。然而，更精确的方法可能涉及动态摩擦模型的识别和补偿。

    5. 重力补偿

    对于多关节机器人来说，重力是一个重要的考虑因素。你的代码中包括了重力补偿的步骤，这是确保机械臂在自由空间中运动时不会因重力而偏离期望轨迹的关键。

    6. 电流环控制

    你提到的方法依赖于电机的电流环控制。这意味着控制算法输出的力矩（或电流）指令被直接发送到电机驱动器，驱动器负责将其转换为实际的电机电流。电流环控制通常具有较快的响应时间，但力控制的精度可能受到电机特性、驱动器性能和机械系统动态特性的影响。

    7. 调试和校准

    尽管你的算法在概念上相对简单，但实现一个稳定且有效的力控系统可能需要大量的调试和校准工作。这包括调整PID控制器的参数、验证雅可比矩阵的正确性、以及确保所有传感器和执行器都正常工作。

    结论

    你的文章为那些希望在机械臂上实现简单力控功能的读者提供了一个很好的起点。尽管这种方法在精度和鲁棒性方面可能无法与更高级的控制策略相媲美，但它为理解和实现更复杂的控制算法提供了宝贵的基础。对于那些希望将机械臂用于交互任务的研究人员和工程师来说，这是一个非常有价值的技能。

    以上为生成回答，仅供参考～

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    @17171680-1 我去这么高，我还是不用astrapro了吧，毕设随便跑一下得了，深度相机后面再自己玩

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