Traceback (most recent call last):
File "/home/ebox12/connect_ws/install/time_communication/lib/time_communication/time_publisher", line 11, in <module>
load_entry_point('time-communication', 'console_scripts', 'time_publisher')()
File "/usr/lib/python3/dist-packages/pkg_resources/init.py", line 490, in load_entry_point
return get_distribution(dist).load_entry_point(group, name)
File "/usr/lib/python3/dist-packages/pkg_resources/init.py", line 2854, in load_entry_point
return ep.load()
File "/usr/lib/python3/dist-packages/pkg_resources/init.py", line 2445, in load
return self.resolve()
File "/usr/lib/python3/dist-packages/pkg_resources/init.py", line 2451, in resolve
module = import(self.module_name, fromlist=['name'], level=0)
File "/home/ebox12/connect_ws/build/time_communication/time_communication/time_publisher.py", line 4, in <module>
from time_communication.msg import TimeData
ModuleNotFoundError: No module named 'time_communication.msg'
daff6682-a791-405f-b75d-24080aa3f823-image.png
setup.py
a3c31ccf-6d6b-4dce-8e9f-5c010ede17d6-image.png
package.xml
74254411-83df-4f39-97da-03d00d3aae30-image.png
TimeData.msg
561a58d7-7430-4889-aa1a-eef0e00e28a4-image.png

现在我们的unitree g1机器人的ip为192.168.123.4，我么的自己的主机ip为192.168.123.123，二者通过网线连接，且可以相互ping通，两个主机都已经关闭了防火墙。
我们需要让192.168.123.4接收到来自192.168.123.123的topic，但是经过尝试，在192.168.123.123运行ros2 run demo_nodes_cpp talker； 在192.168.123.4运行ros2 run demo_nodes_cpp listener ,但是没有正常输出。关于二者的有关ROS的环境变量：

(g1) unitree@ubuntu:</del>/g1_deploy/g1$ printenv | grep ROS
ROS_VERSION=2
ROS_PYTHON_VERSION=3
ROS_DOMAIN_ID=42
ROS_LOCALHOST_ONLY=0
ROS_DISTRO=foxy
(base) franka@franka-HP-Z2-Tower-G9-Workstation-Desktop-PC:<del>/zjm/Livox-SDK2$ printenv | grep ROS
ROS_VERSION=2
ROS_PYTHON_VERSION=3
ROS_DOMAIN_ID=42
ROS_LOCALHOST_ONLY=0
ROS_DISTRO=foxy
想问问可能是什么原因导致192.168.123.123的topic无法正常被192.168.123.4订阅？

bf1756a2-d40f-4b21-a569-ee6c57dcdae4-image.png
69a479b5-ad4a-4ce2-aeaa-903134d37400-image.png
1ed41aac-79a1-43ad-94fa-1cd629c4a743-image.png
944d2d0f-0237-4ced-b347-489e5dc90f21-image.png

大佬们，请教一个问题，我的环境是ros1 noetic。我利用moveit进行运动规划；启动以后，在rviz中的motionplanning中的scene objects添加物体，publish出去以后。我进行运动规划的时候感觉并没有识别到我发布的这个物体。不知道是什么原因；是没有成功发布？还是发布的物体没有看来障碍物？还是需要什么其他的设置呢。

5c3c591c-a5c7-4745-b751-0f3ddd78725d-image.png

《ROS 2机器人开发》书中114页通过节点修改参数，书里面讲述的例子是修改的模型这个参数，如果想修改检测次数upsample_times这个参数应该怎么做，我模仿书中修改模型model参数的例子写了但是不行，请教一下应该怎么办？
是不是SetParameters里面的integer_value不是检测次数
new_model_value.integer_value=int(detect_times)这一行应该是有问题，请教应该怎么修改。

import rclpy from rclpy.node import Node from chapt4_interfaces.srv import FaceDetector from sensor_msgs.msg import Image import cv2 from cv_bridge import CvBridge from rcl_interfaces.srv import SetParameters from rcl_interfaces.msg import Parameter,ParameterValue,ParameterType import time class FaceDetectorClient(Node): def __init__(self,node_name,image_path): super().__init__(node_name) self.client =self.create_client(FaceDetector,'face_detect') self.bridge=CvBridge() self.image_path=image_path self.image =cv2.imread(self.image_path) def send_request(self): while self.client.wait_for_service(timeout_sec=1) is False: self.get_logger().info('服务端未上线...') request=FaceDetector.Request() request.image=self.bridge.cv2_to_imgmsg(self.image) future=self.client.call_async(request) rclpy.spin_until_future_complete(self,future) response=future.result() self.get_logger().info(f'收到响应：图像共有：{response.number}张脸，耗时{response.use_time}') # self.show_face_location(response) def show_face_location(self,response): for i in range(response.number): top =response.top[i] right=response.right[i] bottom=response.bottom[i] left=response.left[i] cv2.rectangle(self.image,(left,top),(right,bottom),(0,0,255),2) cv2.imshow('人脸检测结果',self.image) cv2.waitKey(0) def call_set_parameter(self,parameters): update_param_client=self.create_client(SetParameters,'/face_detect_node/set_parameters') while update_param_client.wait_for_service(timeout_sec=1) is False: self.get_logger().info('等待参数更新服务端上线...') time.sleep(1.0) request=SetParameters.Request() request.parameters=parameters future=update_param_client.call_async(request) rclpy.spin_until_future_complete(self,future) response=future.result() return response def update_detect_model(self,model_name): param=Parameter() param.name='set_model' new_model_value=ParameterValue() new_model_value.type=ParameterType.PARAMETER_STRING new_model_value.string_value=model_name param.value=new_model_value response=self.call_set_parameter([param]) for result in response.results: if result.successful: self.get_logger().info(f'参数{param.name}设置为{model_name}') else: self.get_logger().info(f'参数设置失败，原因为{result.reason}') def update_detect_times(self,detect_times): param=Parameter() param.name='upsample_times' new_model_value=ParameterValue() new_model_value.type=ParameterType.PARAMETER_STRING new_model_value.integer_value=int(detect_times) param.value=new_model_value response=self.call_set_parameter([param]) for result in response.results: if result.successful: self.get_logger().info(f'参数{param.name}设置为{detect_times}') else: self.get_logger().info(f'参数设置失败，原因为{result.reason}') def main(args=None): rclpy.init(args=args) node=FaceDetectorClient('face_detect_client',image_path='/home/bonoit/Desktop/1.jpg') node.update_detect_model('cnn') node.send_request() node.update_detect_model('hog') node.send_request() detect_times=2 node.update_detect_times(detect_times) node.send_request() rclpy.spin(node) node.destroy_node() rclpy.shutdown()

51cfb266-ea72-47a5-b4c5-8f3b4649e5f5-image.png controller_manager:
ros__parameters:
update_rate: 100 # Hz
use_sim_time: true
fishbot_joint_state_broadcaster:
type: joint_state_broadcaster/JointStateBroadcaster
use_sim_time: true
update_rate: 50
rear_wheels_velocity_controller:
type: ackermann_steering_controller/AckermannSteeringController

# left_wheel: "lbj" # 后左轮关节名 # right_wheel: "rbj" # 后右轮关节名 # left_steering: "lftj" # 前轮转向关节 # right_steering: "rftj" #front_steering_joints: ["lftj", "rftj"] # 必须匹配 URDF rear_wheel_joints: ["rbj", "lbj"] front_wheel_joints: ["rfj", "lfj"] wheelbase: 0.63 # 前后轮轴距（米） wheel_radius: 0.075 wheel_separation: 0.88 # 左右轮距（米） max_steer_angle: 0.52 cmd_vel_topic: "/cmd_vel" # 订阅的cmd_vel话题 odom_topic: "/odom" # 发布的里程计话题 odom_frame_id: odom base_frame_id: base_footprint pose_covariance_diagonal: [0.001, 0.001, 0.0, 0.0, 0.0, 0.01] twist_covariance_diagonal: [0.001, 0.0, 0.0, 0.0, 0.0, 0.01] enable_odom_tf: true # 启用odom到base_link的TF变换 cmd_vel_timeout: 0.5 # 指令超时时间（秒） publish_rate: 50.0 # 发布频率（Hz） use_stamped_vel: false # 不使用时间戳速度指令 open_loop: true # 前轮转向控制器（位置控制） fishbot_front_wheels_position_controller: type: position_controllers/JointGroupPositionController

fishbot_front_wheels_position_controller:
ros__parameters:

joints: ["lftj","rftj"] command_interfaces: ["position"] state_interfaces: ["position"]

检查了一下指标，发现没怎么有问题，自己调了半天也没调上来，该怎么办呀？
d7d2c2fb-e470-4b09-ad5b-b09d10be2c8b-image.png

标题：机械臂在gazebo里面仿真，rviz里面的姿态和gazebo不一样（ros2 humble，gazebo classic） 背景(可选)：

我目前正在学习通过ros2驱动机械臂实现抓取的功能，目前的阶段是想实现在gazebo里面进行仿真

问题描述： 我想要在gazebo里面进行仿真，实现机械臂末端有夹爪能够夹取东西，但是目前在rivz里面显示的效果和在gazebo里面是不一样的，问题就是gazebo显示的画面里，桌子是一直抖动的状态，机械臂在gazebo里面也是瘫软无力的，需要怎么解决 具体细节和上下文：

f10fd21d-2d92-41f3-97a9-100c4bea9319-image.png
3420f2c2-016d-4da3-91b7-1fb866d945f5-image.png

尝试过的解决方法：

具体的就是修改了urdf文件，修改了桌子的惯性参数，但是也不确定自己修改的是不是对的，问过老师，老师说我需要添加controller，但是也不知道做，没有一个大体的思路

e1d744a8-c2f1-4092-a3c9-63c5000e7532-ccadef6b-38e3-4d46-a578-a643ddc21c77.png

下面是我的代码
import launch
import launch_ros
from ament_index_python.packages import get_package_share_directory
import os
import launch_ros.parameter_descriptions

def generate_launch_description():
urdf_package_path=get_package_share_directory('fishbot_description')
default_urdf_path=os.path.join(urdf_package_path,'urdf','first_robot.urdf')

action_declare_arg_mode_path=launch.actions.DeclareLaunchArgument( name='model',default_value=str(default_urdf_path),description='加载的模型文件路径' ) substitutions_result=launch.substitutions.Command(['cat ',launch.substitutions.launch_configuration('model')]) robot_description_value=launch_ros.parameter_descriptions.ParameterValue(substitutions_result,value_type=str) action_robot_state_publisher=launch_ros.actions.Node( package='robot_state_publisher', executable='robot_state_publisher', parameters=[{'robot_description':robot_description_value}] ) action_joint_state_publisher=launch_ros.actions.Node( package='joint_state_publisher', executable='joint_state_publisher', ) action_rviz_node=launch_ros.actions.Node( package='rviz2', executable='rviz2', ) return launch.launch_description([ action_declare_arg_mode_path, action_robot_state_publisher, action_joint_state_publisher, action_rviz_node, ])

请问，ROS2 humble能否设置日志文件大小且实现轮转，就是存储日志到文件到达一定大小后，新建文件存储后续内容

ros2 FollowWaypoints action server is not available （ros2 foxy版本 ubuntu20）

但ros2命令执行发现 FollowWaypoint 的node action service都在
而且rviz2是可以做导航的。（按钮驱动）
用的是navigation2 (humble的)
主要代码如下：
from geometry_msgs.msg import PoseStamped
from nav2_simple_commander.robot_navigator import BasicNavigator, TaskResult
import rclpy
from rclpy.duration import Duration
import tf_transformations

def main():
rclpy.init()

navigator = BasicNavigator() # 位置初始化 # initial_pose = PoseStamped() # initial_pose.header.frame_id = 'map' # initial_pose.header.stamp = navigator.get_clock().now().to_msg() # initial_pose.pose.position.x = 3.45 # initial_pose.pose.position.y = 2.15 # initial_pose.pose.orientation.z = 1.0 # initial_pose.pose.orientation.w = 0.0 # navigator.setInitialPose(initial_pose) navigator.waitUntilNav2Active() #添加导航点 goal_poses = [] goal_pose1 = PoseStamped() goal_pose1.header.frame_id = 'map' goal_pose1.header.stamp = navigator.get_clock().now().to_msg() goal_pose1.pose.position.x = 1.5 goal_pose1.pose.position.y = -0.55 yaw=0 quat=tf_transformations.quaternion_from_euler(0,0,yaw) goal_pose1.pose.orientation.x = quat[0] goal_pose1.pose.orientation.y = quat[1] goal_pose1.pose.orientation.z = quat[2] goal_pose1.pose.orientation.w = quat[3] goal_poses.append(goal_pose1) goal_pose2 = PoseStamped() goal_pose2.header.frame_id = 'map' goal_pose2.header.stamp = navigator.get_clock().now().to_msg() goal_pose2.pose.position.x = 0.3 goal_pose2.pose.position.y = -0.2 yaw=0 quat=tf_transformations.quaternion_from_euler(0,0,yaw) goal_pose2.pose.orientation.x = quat[0] goal_pose2.pose.orientation.y = quat[1] goal_pose2.pose.orientation.z = quat[2] goal_pose2.pose.orientation.w = quat[3] goal_poses.append(goal_pose2) goal_pose3 = PoseStamped() goal_pose3.header.frame_id = 'map' goal_pose3.header.stamp = navigator.get_clock().now().to_msg() goal_pose3.pose.position.x = -0.8 goal_pose3.pose.position.y = -0.3 yaw=0 quat=tf_transformations.quaternion_from_euler(0,0,yaw) goal_pose3.pose.orientation.x = quat[0] goal_pose3.pose.orientation.y = quat[1] goal_pose3.pose.orientation.z = quat[2] goal_pose3.pose.orientation.w = quat[3] goal_poses.append(goal_pose3) nav_start = navigator.get_clock().now() navigator.followWaypoints(goal_poses)

雷达自带imu，机器人自身也有配imu，当前雷达是倾斜放置的，为了有一定高度同时探测地面低矮的障碍物，尝试了一些配置，有以下问题
1：如果tracking_frame配置为base_link，会报错，要求imu的frame id和base_link不能离太远，3d建图配置里没找到哪里可以禁用imu
2：如果tracking_frame配置为imu的frame id，则rviz中map会倾斜，导致地图都是灰色或黑色

两个imu都没有和base_link重合

0a8915de-36bc-4427-93aa-adc66e8f6b7c-image.png

请教大家个问题，在ros2的导航配置文件中，如何对规划好的全局路径进行平滑优化呢？如何在BT行为树中添加smoother_path节点？

就是我用 nc -l 8889 小车不会显示 hello fishros 然后我看雷达板上 的ip 也没了 #

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 60, in main from tools.base import CmdTask,FileUtils,PrintUtils,ChooseTask,ChooseWithCategoriesTask,Tracking ImportError: cannot import name 'CmdTask' from 'tools.base' (/tmp/fishinstall/tools/base.py)

4d00eb253db5251d8d9e682f7445fac.png
6.4.2 安装sudo apt install ros-$ROS_DISTRO-gazebo-ros-pkgs这个功能包的时候安装失败，是不是安装包被删除了啊

3d1f36c5-d9ea-4f6c-ad93-218f527fd241-449647d2b480ebcc08d674dba2c2dee.png

应该是gpu方面gazebo和wsl2有冲突，实测把gazebo换成cpu渲染可以正常运行，但一运行cpu占用就90%，电脑风扇呼呼响，不是个办法，想问下有大佬知道怎么办吗

具体报错信息为[Err] [Model.cc:1160] Exception occured in the Load function of plugin with name[gazebo_ros2_control] and filename[libgazebo_ros2_control.so]. This plugin will not run.
[ERROR] [gzserver-2]: process has died [pid 4992, exit code -11, cmd 'gzserver /home/sy/ros2/chapt6/chapt6_ws/install/fishbot_description/share/fishbot_description/world/custom_room.world --verbose -slibgazebo_ros_init.so -slibgazebo_ros_factory.so -slibgazebo_ros_force_system.so'].
[gzserver-2]
不启用这个插件就不会报错，fishbot.ros2_control.xacro中的代码：
<?xml version="1.0"?>
<robot xmlns:xacro="http://www.ros.org/wiki/xacro">
<xacro:macro name="fishbot_ros2_control">
<ros2_control name="FishBotGazeboSystem" type="system">
<hardware>
<plugin>gazebo_ros2_control/GazeboSystem</plugin>
</hardware>
<joint name="left_wheel_joint">
<command_interface name="velocity">
<param name="min">-1</param>
<param name="max">1</param>
</command_interface>
<command_interface name="effort">
<param name="min">-0.1</param>
<param name="max">0.1</param>
</command_interface>
<state_interface name="position" />
<state_interface name="velocity" />
<state_interface name="effort" />
</joint>
<joint name="right_wheel_joint">
<command_interface name="velocity">
<param name="min">-1</param>
<param name="max">1</param>
</command_interface>
<command_interface name="effort">
<param name="min">-0.1</param>
<param name="max">0.1</param>
</command_interface>
<state_interface name="position" />
<state_interface name="velocity" />
<state_interface name="effort" />
</joint>
</ros2_control>
<gazebo>
<plugin filename="libgazebo_ros2_control.so" name="gazebo_ros2_control">
<parameters>$(find fishbot_description)/config/fishbot_ros2_controller.yaml</parameters>
</plugin>
</gazebo>
</xacro:macro>
</robot>

fishbot_ros2_controller.yaml：
controller_manager:
ros__parameters:
update_rate: 100.0
use_sim_time: true

使用鱼哥第七章的fishbot_navigation2功能包想做实体小车导航。问题是2D pose estimate后全局代价地图和局部代价地图始终不显示，请鱼哥和各位大佬看看我朝哪个方向排查：

详细描述如下：
1.版本：ROS2 jazzy ubuntu24.04 树莓派5。激光雷达是实体单线雷达 自己搓的麦轮小车，能发布里程计（自己测试还挺准的）
2.使用里程计小车能找到自己的位置，配合雷达能完成家里客厅的简单建图
3.nav2_params.yaml 和 navigation2.launch.py（这个launch里调用了nav2_bringup，传参是map_yaml_path，use_sim_time，和yaml文件路径）是在鱼哥的基础上改的，主要修改的1）use_sim_time: False 2）没有URDF，所以发布了一个 1hz的base_footprint->base_link->laser的TF 3）其他小的参数改动
4.运行navigation2.launch.py后，查看TF都正常，2Dpose estimate后能看到周围有粒子（看样子负责定位的自适应蒙特卡洛粒子滤波起作用了），但是代价地图（全局 局部）都不显示 代价地图模块说no map received
5.显然在代价地图说收不到map的情况下点NAV2 GOAL也是无效的 terminal说 没有设置起始位置（但是其实我设置了）

6 补充：我在目前的基础上丧心病狂的再运行一下ros2 launch nav2_bringup navigation_launch.py 代价地图就有了（代价有点大 我家客厅有点小😕 ），但是NAV2 GOAL还是失败

请各位大佬指点一二，帮我看看我的问题可能在哪：

**问题1 我没有代价地图的问题可能在哪？
初始位置没设置对？（AMCL模块正常，TF显示map->odom）
代价地图的YAML没配置对？（我跑鱼哥的yaml仿真能跑，仅仅改了footprint坐标系和仿真时间）
为什么我运行ros2 launch nav2_bringup navigation_launch.py 能出代价地图？

问题2 我运行ros2 launch nav2_bringup navigation_launch.py 显然是不应该有的做法，让节点重复发布了。这时候不能导航仅仅是因为节点重复发布的原因吗？还是我还有一些别的没做对？**

Screenshot 2025-06-29 121845.png
这是点2d pose estimate后的结果
Screenshot 2025-06-29 134036.png
这是此时的TF
TOPIC_RQT.png
这是此时的节点
状态反馈qt.png
这是小车反馈信息 里程计发布应该都正常（这个图是我后截取的，用遥控器控制小车 确认小车发布的里程计有效）
问题描述.png
这个是再没有代价地图的情况下强行点NAV2GOAL的结果
Screenshot 2025-06-29 143155.png
这个是运行一遍ros2 launch nav2_bringup navigation_launch.py 后的结果，注意此时节点几乎都存在两个同名节点，不知道不能导航是否和同名节点有关，但是起码运行这个显示代价地图了
Screenshot 2025-06-29 143330.png
这个是在运行ros2 launch nav2_bringup navigation_launch.py后有代价地图 点NAV2 goal的结果

下面是我的nav2_params.yaml
amcl:
ros__parameters:
use_sim_time: False
alpha1: 0.2
alpha2: 0.2
alpha3: 0.2
alpha4: 0.2
alpha5: 0.2
base_frame_id: "base_footprint"
beam_skip_distance: 0.5
beam_skip_error_threshold: 0.9
beam_skip_threshold: 0.3
do_beamskip: false
global_frame_id: "map"
lambda_short: 0.1
laser_likelihood_max_dist: 2.0
laser_max_range: 100.0
laser_min_range: -1.0
laser_model_type: "likelihood_field"
max_beams: 60
max_particles: 2000
min_particles: 500
odom_frame_id: "odom"
pf_err: 0.05
pf_z: 0.99
recovery_alpha_fast: 0.0
recovery_alpha_slow: 0.0
resample_interval: 1
robot_model_type: "nav2_amcl::DifferentialMotionModel"
save_pose_rate: 0.5
sigma_hit: 0.2
tf_broadcast: true
transform_tolerance: 1.0
update_min_a: 0.2
update_min_d: 0.25
z_hit: 0.5
z_max: 0.05
z_rand: 0.5
z_short: 0.05
scan_topic: scan

bt_navigator:
ros__parameters:
use_sim_time: False
global_frame: map
robot_base_frame: base_footprint
odom_topic: /odom
bt_loop_duration: 10
default_server_timeout: 20
# 'default_nav_through_poses_bt_xml' and 'default_nav_to_pose_bt_xml' are use defaults:
# nav2_bt_navigator/navigate_to_pose_w_replanning_and_recovery.xml
# nav2_bt_navigator/navigate_through_poses_w_replanning_and_recovery.xml
# They can be set here or via a RewrittenYaml remap from a parent launch file to Nav2.
plugin_lib_names:
- nav2_compute_path_to_pose_action_bt_node
- nav2_compute_path_through_poses_action_bt_node
- nav2_smooth_path_action_bt_node
- nav2_follow_path_action_bt_node
- nav2_spin_action_bt_node
- nav2_wait_action_bt_node
- nav2_assisted_teleop_action_bt_node
- nav2_back_up_action_bt_node
- nav2_drive_on_heading_bt_node
- nav2_clear_costmap_service_bt_node
- nav2_is_stuck_condition_bt_node
- nav2_goal_reached_condition_bt_node
- nav2_goal_updated_condition_bt_node
- nav2_globally_updated_goal_condition_bt_node
- nav2_is_path_valid_condition_bt_node
- nav2_initial_pose_received_condition_bt_node
- nav2_reinitialize_global_localization_service_bt_node
- nav2_rate_controller_bt_node
- nav2_distance_controller_bt_node
- nav2_speed_controller_bt_node
- nav2_truncate_path_action_bt_node
- nav2_truncate_path_local_action_bt_node
- nav2_goal_updater_node_bt_node
- nav2_recovery_node_bt_node
- nav2_pipeline_sequence_bt_node
- nav2_round_robin_node_bt_node
- nav2_transform_available_condition_bt_node
- nav2_time_expired_condition_bt_node
- nav2_path_expiring_timer_condition
- nav2_distance_traveled_condition_bt_node
- nav2_single_trigger_bt_node
- nav2_goal_updated_controller_bt_node
- nav2_is_battery_low_condition_bt_node
- nav2_navigate_through_poses_action_bt_node
- nav2_navigate_to_pose_action_bt_node
- nav2_remove_passed_goals_action_bt_node
- nav2_planner_selector_bt_node
- nav2_controller_selector_bt_node
- nav2_goal_checker_selector_bt_node
- nav2_controller_cancel_bt_node
- nav2_path_longer_on_approach_bt_node
- nav2_wait_cancel_bt_node
- nav2_spin_cancel_bt_node
- nav2_back_up_cancel_bt_node
- nav2_assisted_teleop_cancel_bt_node
- nav2_drive_on_heading_cancel_bt_node
- nav2_is_battery_charging_condition_bt_node

bt_navigator_navigate_through_poses_rclcpp_node:
ros__parameters:
use_sim_time: False

bt_navigator_navigate_to_pose_rclcpp_node:
ros__parameters:
use_sim_time: False

controller_server:
ros__parameters:
use_sim_time: False
controller_frequency: 20.0
min_x_velocity_threshold: 0.001
min_y_velocity_threshold: 0.5
min_theta_velocity_threshold: 0.001
failure_tolerance: 0.3
progress_checker_plugin: "progress_checker"
goal_checker_plugins: ["general_goal_checker"] # "precise_goal_checker"
controller_plugins: ["FollowPath"]

# Progress checker parameters progress_checker: plugin: "nav2_controller::SimpleProgressChecker" required_movement_radius: 0.5 movement_time_allowance: 10.0 # Goal checker parameters #precise_goal_checker: # plugin: "nav2_controller::SimpleGoalChecker" # xy_goal_tolerance: 0.25 # yaw_goal_tolerance: 0.25 # stateful: True general_goal_checker: stateful: True plugin: "nav2_controller::SimpleGoalChecker" xy_goal_tolerance: 0.25 yaw_goal_tolerance: 0.25 # DWB parameters FollowPath: plugin: "dwb_core::DWBLocalPlanner" debug_trajectory_details: True min_vel_x: 0.0 min_vel_y: 0.0 max_vel_x: 0.26 max_vel_y: 0.0 max_vel_theta: 1.0 min_speed_xy: 0.0 max_speed_xy: 0.26 min_speed_theta: 0.0 # Add high threshold velocity for turtlebot 3 issue. # https://github.com/ROBOTIS-GIT/turtlebot3_simulations/issues/75 acc_lim_x: 2.5 acc_lim_y: 0.0 acc_lim_theta: 3.2 decel_lim_x: -2.5 decel_lim_y: 0.0 decel_lim_theta: -3.2 vx_samples: 20 vy_samples: 5 vtheta_samples: 20 sim_time: 1.7 linear_granularity: 0.05 angular_granularity: 0.025 transform_tolerance: 0.2 xy_goal_tolerance: 0.25 trans_stopped_velocity: 0.25 short_circuit_trajectory_evaluation: True stateful: True critics: ["RotateToGoal", "Oscillation", "BaseObstacle", "GoalAlign", "PathAlign", "PathDist", "GoalDist"] BaseObstacle.scale: 0.02 PathAlign.scale: 32.0 PathAlign.forward_point_distance: 0.1 GoalAlign.scale: 24.0 GoalAlign.forward_point_distance: 0.1 PathDist.scale: 32.0 GoalDist.scale: 24.0 RotateToGoal.scale: 32.0 RotateToGoal.slowing_factor: 5.0 RotateToGoal.lookahead_time: -1.0

local_costmap:
local_costmap:
ros__parameters:
update_frequency: 5.0
publish_frequency: 2.0
transform_tolerance: 1.0
global_frame: odom
robot_base_frame: base_footprint
use_sim_time: False
rolling_window: true
static_map: true
width: 1
height: 1
resolution: 0.05
robot_radius: 0.22
plugins: ["voxel_layer", "inflation_layer"]
inflation_layer:
plugin: "nav2_costmap_2d::InflationLayer"
cost_scaling_factor: 3.0
inflation_radius: 0.25
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:
map_topic: /map
plugin: "nav2_costmap_2d::StaticLayer"
map_subscribe_transient_local: True
always_send_full_costmap: True

global_costmap:
global_costmap:
ros__parameters:
update_frequency: 1.0
publish_frequency: 1.0
map_topic: /map
global_frame: map
robot_base_frame: base_footprint
use_sim_time: False
robot_radius: 0.12
resolution: 0.05
track_unknown_space: true
plugins: ["static_layer", "obstacle_layer", "inflation_layer"]
obstacle_layer:
plugin: "nav2_costmap_2d::ObstacleLayer"
enabled: True
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:
map_topic: /map
plugin: "nav2_costmap_2d::StaticLayer"
map_subscribe_transient_local: True
track_unknown_space: true
inflation_layer:
plugin: "nav2_costmap_2d::InflationLayer"
cost_scaling_factor: 3.0
inflation_radius: 0.25
always_send_full_costmap: True

map_server:
ros__parameters:
use_sim_time: False
topic_name: "map"
# Overridden in launch by the "map" launch configuration or provided default value.
# To use in yaml, remove the default "map" value in the tb3_simulation_launch.py file & provide full path to map below.
yaml_filename: ""

map_saver:
ros__parameters:
use_sim_time: False
save_map_timeout: 5.0
free_thresh_default: 0.25
occupied_thresh_default: 0.65
map_subscribe_transient_local: True

planner_server:
ros__parameters:
expected_planner_frequency: 20.0
use_sim_time: False
planner_plugins: ["GridBased"]
GridBased:
plugin: "nav2_navfn_planner/NavfnPlanner"
tolerance: 0.5
use_astar: false
allow_unknown: true

smoother_server:
ros__parameters:
use_sim_time: False
smoother_plugins: ["simple_smoother"]
simple_smoother:
plugin: "nav2_smoother::SimpleSmoother"
tolerance: 1.0e-10
max_its: 1000
do_refinement: True

behavior_server:
ros__parameters:
costmap_topic: local_costmap/costmap_raw
footprint_topic: local_costmap/published_footprint
cycle_frequency: 10.0
behavior_plugins: ["spin", "backup", "drive_on_heading", "assisted_teleop", "wait"]
spin:
plugin: "nav2_behaviors/Spin"
backup:
plugin: "nav2_behaviors/BackUp"
drive_on_heading:
plugin: "nav2_behaviors/DriveOnHeading"
wait:
plugin: "nav2_behaviors/Wait"
assisted_teleop:
plugin: "nav2_behaviors/AssistedTeleop"
global_frame: odom
robot_base_frame: base_footprint
transform_tolerance: 0.1
use_sim_time: False
simulate_ahead_time: 2.0
max_rotational_vel: 1.0
min_rotational_vel: 0.4
rotational_acc_lim: 3.2

robot_state_publisher:
ros__parameters:
use_sim_time: False

waypoint_follower:
ros__parameters:
use_sim_time: False
loop_rate: 20
stop_on_failure: false
waypoint_task_executor_plugin: "wait_at_waypoint"
wait_at_waypoint:
plugin: "nav2_waypoint_follower::WaitAtWaypoint"
enabled: True
waypoint_pause_duration: 200

velocity_smoother:
ros__parameters:
use_sim_time: False
smoothing_frequency: 20.0
scale_velocities: False
feedback: "OPEN_LOOP"
max_velocity: [0.26, 0.0, 1.0]
min_velocity: [-0.26, 0.0, -1.0]
max_accel: [2.5, 0.0, 3.2]
max_decel: [-2.5, 0.0, -3.2]
odom_topic: "odom"
odom_duration: 0.1
deadband_velocity: [0.0, 0.0, 0.0]
velocity_timeout: 1.0

下面是navigation2.launch.py
import os
from ament_index_python.packages import get_package_share_directory
from launch import LaunchDescription
from launch.actions import DeclareLaunchArgument, IncludeLaunchDescription, ExecuteProcess, TimerAction
from launch.substitutions import LaunchConfiguration
from launch.launch_description_sources import PythonLaunchDescriptionSource
from launch_ros.actions import Node

def generate_launch_description():
# 获取包路径
fishbot_navigation2_dir = get_package_share_directory('fishbot_navigation2')
nav2_bringup_dir = get_package_share_directory('nav2_bringup')

# 配置文件路径 map_yaml_path = os.path.join(fishbot_navigation2_dir, 'maps', 'room.yaml') nav2_param_path = os.path.join(fishbot_navigation2_dir, 'config', 'nav2_params.yaml') rviz_config_path = os.path.join(nav2_bringup_dir, 'rviz', 'nav2_default_view.rviz') # Launch参数 use_sim_time = LaunchConfiguration('use_sim_time', default='false') return LaunchDescription([ # 声明参数 DeclareLaunchArgument('use_sim_time', default_value='false', description='Use simulation time'), DeclareLaunchArgument('map', default_value=map_yaml_path, description='Path to map YAML file'), DeclareLaunchArgument('params_file', default_value=nav2_param_path, description='Path to Nav2 parameters file'), # 关键修改1：使用bringup_launch.py并传递所有必要参数 IncludeLaunchDescription( PythonLaunchDescriptionSource([ nav2_bringup_dir, '/launch/bringup_launch.py' ]), launch_arguments={ 'map': map_yaml_path, # 必须保留地图路径 'use_sim_time': use_sim_time, 'params_file': nav2_param_path, 'autostart': 'true', 'enable_rviz': 'false' }.items(), ), # 关键修改2：简化TF发布节点 Node( package='fishbot_navigation2', executable='tf_publisher_1hz.py', name='tf_publisher_1hz', output='screen', parameters=[{ 'use_sim_time': use_sim_time, 'frame_ids': ['map', 'odom', 'base_link'], 'parent_frames': ['', 'map', 'odom'], 'publish_rate': '10.0' }] ), # 启动RViz2（延迟5秒确保所有节点就绪） TimerAction( period=5.0, actions=[ Node( package='rviz2', executable='rviz2', name='rviz2', arguments=['-d', rviz_config_path], parameters=[{'use_sim_time': use_sim_time}], output='screen' ) ] ) ])

请各位帮忙看看，卡很久了这里 GPT给的方法几乎都试了，无果。