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ROSMASTER M1 PRO📖
0.Robot Configuration and Operation Guidelines
  • 0.Unboxing and Review
  • 1.Assembly Videos
  • 2.User Manual
  • 3.Enter Docker (For Raspberry Pi)
  • 4.FAQ
  • 5.RobotManager User Guide
1.Chassis Control Course
  • 1.Robot Information Publishing
  • 2.Robot Handle Control
  • 3.Robot Keyboard Control
  • 4.Linear Velocity Calibration
  • 5.Angular Velocity Calibration
  • 6.Robot URDF Model
  • 7.Robot EKF State Estimation
2.Lidar Course
  • 1.Lidar Introduction And Use
  • 2.Lidar Obstacle Avoidance
  • 3.Lidar Following
  • 4.Lidar Guard
  • 5.Lidar Patrol
  • 6.GMapping-SLAM Mapping
  • 7.Cartographer-SLAM Mapping
  • 8.Slam-Toolbox Mapping
  • 9.Lifelong Mode Mapping
  • 10.Navigation2 Single Point Navigation
  • 11.Navigation2 Multi Point Navigation
  • 12.Cartographer Relocalization Navigation
  • 13.Slam-Toolbox Localization Navigation
  • 14.Synchronous Mapping And Navigation
  • 15.Aruco Visual Relocalization Navigation
  • 16.Mobile App Mapping And Navigation
3.USB Camera-Depth Camera Course
  • 1.USB Camera Introduction
  • 2.USB Camera Intrinsic Calibration
  • 3.Nuwa-HP60C Camera Introduction (Depth Camera Only)
  • 4.Depth Pseudo Color Image (Depth Camera Only)
  • 5.Depth Camera Distance Measurement (Depth Camera Only)
  • 6.Block Volume Calculation (Depth Camera Only)
  • 7.Edge Detection (Depth Camera Only)
  • 8.RTAB-Map SLAM Mapping (Depth Camera Only)
  • 9.RTAB-Map Navigation (Depth Camera Only)
4.Robotic Arm and 3D Space Gripping Course
  • 1.Robotic Arm Basic Usage
  • 2.Robotic Arm Kinematics
  • 3.Robotic Arm Chassis Coordination Control
  • 4.AprilTag ID Sorting
  • 5.AprilTag Height Anomaly Sorting
  • 6.AprilTag Tracking and Grasping
  • 7.Color Block Sorting
  • 8.Color Block Height Anomaly Sorting
  • 9.Color Block Tracking and Grasping
  • 10.Wood Block Shape Sorting
  • 11.KCF Tracking and Grasping Objects
  • 12.Mediapipe Gesture ID Sorting AprilTag
  • 13.Mediapipe Gesture Height Sorting AprilTag
  • 14.Desktop Tracking and Grasping AprilTag
  • 15.3D Spatial Tracking AprilTag
  • 16.Transformer Model Tracking Algorithm
  • 17.Line Following Obstacle Clearing
5.Road network planning and navigation
  • 1.Introduction To Road Network Planning
  • 2.Road Network Annotation
  • 3.Planning And Navigation Between Waypoints
  • 4.Road Network Navigation In Any Pose
  • 5.Path Re-planning
6.OpenClaw Basic Course
  • 1.Introduction to OpenClaw
  • 2.OpenClaw Core Concepts
  • 3.OpenClaw API-KEY Configuration
  • 4.OpenClaw Switch Models
  • 5.OpenClaw System Prompt Words
  • 6.OpenClaw Common CLI Commands
7.OpenClaw Interaction Method
  • 1.OpenClaw Webchat Interaction
  • 2.OpenClaw Tui Interaction
  • 3.OpenClaw Voice Dialogue Interaction
  • 4.OpenClaw WhatsApp Interaction
8.OpenClaw Development
  • 1.OpenClaw Connecting to Robot MCP Service
  • 2.Robot CLI Command Tool
  • 3.robot-control Plugin Tool
  • 4.reply-bridge Plugin Tool
  • 5.OpenClaw Multimodal Vision
  • 6.OpenClaw Chassis Control
  • 7.OpenClaw Robotic Arm Control
  • 8.OpenClaw Skills Development
  • 9.OpenClaw Scheduled Tasks
  • 10.OpenClaw Multi-Agent Intelligent Agent
  • 11.OpenClaw Active Interaction
  • 12.OpenClaw Vector Memory
9.OpenClaw Embodied intelligent application
  • 1.OpenClaw Target Tracking
  • 2.OpenClaw Arm Tracking And Grasping
  • 3.OpenClaw Arm Fixed-point Placement
  • 4.OpenClaw Waste Sorting
  • 5.OpenClaw SLAM Mapping And Navigation
  • 6.OpenClaw Navigation Transport
  • 7.OpenClaw AprilTag Grasping
  • 8.OpenClaw Color Line Patrol
  • 9.OpenClaw Visual Distance Measurement
10.OpenClaw scenario sandbox
  • 1.Map Description and Props Placement
  • 2.Building the Sandbox Map
  • 3.Visual Relocalization Marker
  • 4.Map Mapping Marker
  • 5.Sandbox Scenario Comprehensive Case
11.AI Large Model Basics
  • 1.AI Large Model Types and Principles
  • 2.RAG Retrieval Enhancement and Model Training Samples
  • 3.Embodied Intelligent Robot System Architecture
  • 4.Embodied Intelligent Functions Core Source Code
12.AI large Model Development
  • 1.Register a Model Service Provider Account
  • 2.Configuring API-KEY
  • 3.Introduction to Dify
  • 4.Basic Dify Features
  • 5.AI Large Model Development - Chatbot
  • 6.Deploy the RAG Knowledge Base
  • 7.RAG Knowledge Base + Chatbot
  • 8.AI Agent Workflow
  • 9.Custom Wake-up Response
13.AI Model - Voice Version
  • 1.Semantic Understanding and Command Following
  • 2.Multimodal Visual Understanding
  • 3.Multimodal Visual Understanding and Robotic Arm Gripping
  • 4.Multimodal Visual Understanding and SLAM Navigation
  • 5.Robotic arm gripping+Multimodal visual understand+SLAM navigation
  • 6.Intention Understanding
14.AI Model - Text Version
  • 1.Semantic Understanding and Command Following
  • 2.Multimodal Visual Understanding
  • 3.Multimodal Visual Understanding and Robotic Arm Gripping
  • 4.Multimodal Visual Understanding and SLAM Navigation
  • 5.Robotic arm gripping+Multimodal visual understand+SLAM navigation
  • 6.Intention estimation
15.Mediapipe Visual Course
  • 1.Hand detection
  • 2.Posture detection
  • 3.Overall detection
  • 4.Facial Landmark Detection
  • 5.Face detection
  • 6.Face special effects
  • 7.3D object recognition
  • 8.Brush
  • 9.Finger control
  • 10.Palm target positioning
  • 11.Fingertip trajectory recognition
  • 12.Fingertip gesture control robotic arm
  • 13.Gesture grabbing and releasing objects
  • 14.Finger control robotic arm
  • 15.Medipipe gesture control robotic arm action group
16.MoveIt2 Simulation Course
  • 1.MovelT2 configuration
  • 2.MovelT2 simulation-reality linkage
  • 3.Random movement
  • 4.Forward kinematics design
  • 5.Inverse kinematics design
  • 6.Cartesian path
  • 7.Trajectory Planning
  • 8.Collision Detection
  • 9.Scene Design
  • 10.3D perception obstacle‑avoidance
17.Multi-vehicle Course
  • 1.Multi-vehicle Control
  • 2.Multi-vehicle Navigation
  • 3.Multi-vehicle Formation
18.YOLO26 Development
  • 1.CLI Use
  • 2.Object Detection
  • 3.Instance Segmentation
  • 4.Pose Estimation
  • 5.Image Classification
  • 6.Oriented Object Detection
  • 7.YOLOv26 + DeepSORT Tracking
  • 8.Monocular Depth Estimation
19.Control Board STM32 Driver Course
  • 0.Notes (Must Read)
  • 1.About Expansion Board
  • 2.STM32 Development Environment
  • 3.Button Control
  • 4.FreeRTOS Application
  • 5.Serial Communication
  • 6.SBUS Model Aircraft Remote Control
  • 7.CAN Bus Communication
  • 8.RGB Colorful Light Bar
  • 9.Timer Interrupt to Control PWM Servo
  • 10.Control Serial Port Servos
  • 11.Nine-axis Attitude Sensor to Obtain Data
  • 12.Control Motor
  • 13.Timer Captures the Encoder Data
  • 14.1 Kinematic Analysis of Mecanum Wheel
  • 14.2 Kinematic Analysis of Ackerman
  • 14.3 Kinematic Analysis of 4WD
  • 15.PID Control Robot Movement
20.Docker Course
  • 1.Docker Introduction and Installation
  • 2.Docker Basic Commands
  • 3.Docker Submission and Multi-Terminal Access
  • 4. Docker Startup Script
  • 5.Docker-Vscode Environment Construction
21.Image Processing Basics Course
  • 1. Introduction to Open Source CV
  • 2. Image reading and display
  • 3. Image writing
  • 4. Image quality
  • 5. Pixel Operation
  • 6. Image zoom
  • 7. Image cutting
  • 8. Image translation
  • 9. Image Mirroring
  • 10. Affine Transformation
  • 11. Image Rotation
  • 12. Perspective Transformation
  • 13. Grayscale processing
  • 14. Image Binarization
  • 15. Edge Detection
  • 16. Line drawing
  • 17. Rectangle and circle drawing
  • 18. Drawing text and pictures
22.Linux System Course
  • 1.Introduction to Linux system
  • 2.Ubuntu file system
  • 3.Ubuntu common commands
  • 4.Ubuntu common editors
  • 5.Ubuntu software operation commands
  • 6.Virtual machine installation
  • 7.SSH remote control
  • 8.VNC remote control
  • 9.Transfer files remotely
  • 10.Driver library and communication
  • 11.Static IP and hotspot mode
  • 12.Bind device ID
  • 13.Capacity expansion and resource allocation
  • 14.Update system software sources
  • 15.Set root user password
  • 16.sudo free password
  • 17.Connect to WiFi network
  • 18.View system version
  • 19.Customized service management
  • 20.Back up system image
23.ROS2 Basic Course
  • 1.Introduction to ROS2
  • 2.ROS2 install Humble
  • 3.ROS2 development environment
  • 4.ROS2 workspace
  • 5.ROS2 function package
  • 6.ROS2 node
  • 7.ROS2 topic communication
  • 8.ROS2 service communication
  • 9.ROS2 action communication
  • 10.ROS2 custom interface message
  • 11.ROS2 parameter service case
  • 12.ROS2 meta-function package
  • 13.ROS2 distributed communication
  • 14.ROS2 DDS
  • 15.ROS2 time related API
  • 16.ROS2 common command tools
  • 17.ROS2 rviz2 use
  • 18.ROS2 rqt toolbox
  • 19.ROS2 Launch startup file configuration
  • 20.ROS2 recording and playback tool
  • 21.ROS2 URDF model
  • 22.ROS2 Gazebo simulation platform
  • 23.ROS2 TF2 coordinate transformation
24.Main Control Course
Jetson Orin Nano_NX
  • 1.Jetson Orin board introduction
  • 2.Restore the factory image system
  • 3.Backup SSD system
  • 4.SSD expansion
  • 5.Network configuration
  • 6.SSH remote login
  • 7.VNC remote control
  • 8.Remote file transfer
  • 9.Jtop tool
  • 10.Exchange space expansion
Raspberry Pi
  • 1. Introduction to Raspberry PI 5
  • 2. Raspberry PI system installation and backup
  • 3. Powering the Raspberry PI 5
  • 4. Startup of Raspberry PI 5
  • 5. Update and upgrade operating system
  • 6. Introduction to raspi-config tool
  • 7. config.txt file description
  • 8. Network Configuration
  • 9. remote access
  • 10. Transfer files remotely
  • 11. Set display resolution and rotation
  • 12. Set screen to sleep
  • 13. Play audio and video
  • 14. Using USB camera
  • 15. Using MIPI camera
  • 16. Get real-time temperature of Raspberry Pi
RDKX5
  • 1.Introduction to RDK X5 board
  • 2.Write system file
  • 3.Hardware interface description
  • 4.Install case and other accessories
  • 5.Network configuration
  • 6.Remote login
  • 7.Update system
  • 8.srpi-config user guide
  • 9.config. txt configuration file
  • 10.Self-startup setting
  • 11.RDK exclusive command usage
  • 12.Linux command usage
  • 13.GPIO readwrite operation
  • 14.Image classification algorithm
  • 15.Use USB camera
  • 16.Use MIPI camera
  • 17.Binocular camera depth algorithm
  • 18. Controlling RGB Cooling Fans
Download
  • System File
  • Code
  • 3D Model File
  • Software Tools
  • Hardware_Info
  • Deb function package
  • Dify AI Agent
Download ZIP

Welcome to ROSMASTER M1 PRO repository

1.Robot Information Publishing

ROS Control

ROS Control1. Course Content2. Preparation3. Case Demonstration3.1 Chassis Sensor Topics3.2 Control the Robot Chassis via Topics3.3 Get the Battery Voltage3.4 Get the Chassis Control Board Firmware Version3.5 Get All Joint Angles of the Robotic Arm3.6 Robotic Arm Joint Angle Control3.6.1 Control the Robotic Arm via Topic3.6.2 Control the Robotic Arm via Service3.6.3 Restore the Robotic Arm to Its Initial Pose via Service3.7 Robotic Arm Torque Control3.8 Control Movement via Services3.9 Save a Camera Image via Service4. Core Source Code Analysis

1. Course Content

  • Learn the basic methods for controlling the robot through ROS.

  • This feature controls the car's velocity, buzzer, and robotic arm through the ros2 topic tools, and also reads low-level data such as LiDAR data, IMU data, odometry data, and so on.

2. Preparation

  • Start the basic nodes: chassis serial communication, robot URDF model, LiDAR, and so on.

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ros2 launch yahboomcar_bringup car_base.launch.py use_camera:=true

3. Case Demonstration

3.1 Chassis Sensor Topics

  • Topic summary

TopicMessage TypeDescription
imusensor_msgs/ImuIMU angular velocity + linear acceleration
odom_rawnav_msgs/OdometryAccumulated wheel odometry value
scansensor_msgs/LaserScanLiDAR scan data
  • View all topics

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ros2 topic list

image-20260622111422644

  • Subscribed topics

Subscribed TopicMessage TypeTopic Function
/Buzzerstd_msgs/msg/BoolControl the buzzer
/arm6_jointsarm_msgs/msg/ArmJointsControl the 6 servos of the robotic arm
/arm_jointarm_msgs/msg/ArmJointControl a single servo of the robotic arm
/cmd_velgeometry_msgs/msg/TwistControl the car's velocity
  • Published topics

Published TopicTopic Message TypeTopic Attribute
/imu/data_rawsensor_msgs/msg/ImuPublish IMU data
/odomnav_msgs/msg/OdometryOdometry data
/scansensor_msgs/msg/LaserScanLiDAR data
  • View the publishing rate of a specified topic:

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ros2 topic hz /imu/data_raw

image-20260826180641087

  • View the data content of a specified topic

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ros2 topic echo /imu/data_raw --once

image-20260826180744816

Tip

The command format for viewing the data content, rate, and other information of other topics is the same — just replace the corresponding topic name.

3.2 Control the Robot Chassis via Topics

Use a command in the following format to publish a single frame of control data: ros2 topic pub <topic_name> <topic_message_type> <message_data> --once

Note

  • It is recommended to lift the chassis off the ground before performing topic movement tests.

  • Publishing a velocity command to /cmd_vel controls the car's movement:

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# Move forward along the x-axis at 0.3 m/s
ros2 topic pub /cmd_vel geometry_msgs/msg/Twist "{linear: {x: 0.3}, angular: {z: 0.0}}"

Publishing cmd_vel linear velocity

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# Turn left in place at 1.0 rad/s
ros2 topic pub /cmd_vel geometry_msgs/msg/Twist "{angular: {z: 1.0}}"

Publishing cmd_vel angular velocity

  • Stop the car's movement

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ros2 topic pub /cmd_vel geometry_msgs/msg/Twist "{linear: {x: 0.0}, angular: {z: 0.0}}"

3.3 Get the Battery Voltage

Important

  • If the buzzer keeps beeping "di-di-di——", the battery level is too low and the battery needs to be charged.

  • For lithium batteries, the battery level and the voltage are not in a linear relationship.

  • The normal battery voltage range is 10.3V~12V; when it drops below 10.3V, a reminder is given through the buzzer.

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ros2 service call /get_battery_voltage std_srvs/srv/Trigger

image-20260622115001878

3.4 Get the Chassis Control Board Firmware Version

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ros2 service call /get_car_edition std_srvs/srv/Trigger

image-20260622115059663

3.5 Get All Joint Angles of the Robotic Arm

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ros2 service call /get_arm_joints interfaces/srv/ArmPosition "{}"

image-20260622115230354

3.6 Robotic Arm Joint Angle Control

3.6.1 Control the Robotic Arm via Topic

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ros2 topic pub --once /arm6_joints arm_msgs/msg/ArmJoints "{joint1: 90, joint2: 90, joint3: 90, joint4: 90, joint5: 90, joint6: 30, time: 2000}"

image-20260826181845389

3.6.2 Control the Robotic Arm via Service

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ros2 service call /set_arm_joints interfaces/srv/ArmPosition "{request_joints: [90, 150, 12, 20, 90, 30]}"

image-20260826182003807

3.6.3 Restore the Robotic Arm to Its Initial Pose via Service

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ros2 service call /reset_arm_pose std_srvs/srv/Trigger

image-20260826185828147

3.7 Robotic Arm Torque Control

  • Disable torque

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ros2 service call /set_arm_torque std_srvs/srv/SetBool "{data: false}"

After the robotic arm torque is disabled, the arm joints can be moved slowly by hand.

image-20260826182206446

  • Enable torque

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ros2 service call /set_arm_torque std_srvs/srv/SetBool "{data: true}"

image-20260826182429159

3.8 Control Movement via Services

  • Control the chassis to move or rotate by a precise angle through an action service (closed-loop control based on odometry).

Note

Parameter description:

direction: movement direction; distance: movement distance; angle: rotation angle

  • Usage examples

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# Move forward 0.15 m
ros2 action send_goal /move_by_odom interfaces/action/MoveByOdom "{direction: 'forward', distance: 0.15}"
# Move backward 0.3 m
ros2 action send_goal /move_by_odom interfaces/action/MoveByOdom "{direction: 'backward', distance: 0.3}"

image-20260826182657207

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# Turn left 90 degrees
ros2 action send_goal /move_by_odom interfaces/action/MoveByOdom "{direction: 'turn_left', angle: 90.0}"
# Turn right 45 degrees
ros2 action send_goal /move_by_odom interfaces/action/MoveByOdom "{direction: 'turn_right', angle: 45.0}"

image-20260826182844419

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# Strafe left 0.3 m
ros2 action send_goal /move_by_odom interfaces/action/MoveByOdom "{direction: 'left', distance: 0.3}"
# Strafe right 0.3 m
ros2 action send_goal /move_by_odom interfaces/action/MoveByOdom "{direction: 'right', distance: 0.3}"

3.9 Save a Camera Image via Service

  • Save the most recent image from the camera's video stream.

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ros2 service call /save_image std_srvs/srv/Trigger

image-20260826192205196

Default image save path: $HOME/yahboomcar_ros2_ws/yahboomcar_ws/cache/image.png. You can view the saved image at that path.

image-20260826192346855

image-20260826192430569

4. Core Source Code Analysis

  • Source code path

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$HOME/yahboomcar_ros2_ws/yahboomcar_ws/src/yahboomcar_bringup/yahboomcar_bringup/mcnamu_driver.py
  • The code is fairly long, so only some key parts are explained here.

1. _odom_linear_move — Odometry-based linear motion control

  • goal_handle.request: gets the Action goal request and extracts the movement distance distance and direction direction.

  • Validates whether the direction parameter is one of forward / backward / left / right; if invalid, aborts the goal and returns failure.

  • Defines deceleration thresholds: within < 0.1 m of the target, use the minimum speed 0.07 m/s; between 0.1~0.3 m, decelerate linearly; > 0.3 m, run at full speed.

  • In the main control loop, checks for timeout and cancel requests, calculates the current Euclidean odometry distance moved, and marks success once the target distance is reached.

  • Decelerates in stages according to the remaining distance, maps the direction to x/y velocity components, and calls set_car_motion to send velocity commands.

2. Buzzercallback — Buzzer control callback

  • Subscribes to the /Buzzer topic with message type Bool.

  • When msg.data is True, calls set_beep(1) to turn the buzzer on; when it is False, calls set_beep(0) to turn it off.

3. arm_callback — 6-joint robotic arm angle control callback

  • Extracts the 6 joint angles from the ArmJoints message and assembles them into an angle list.

  • Checks each joint angle one by one against the allowed range self.bounds; if it is out of range, clamps it to the valid range and prints a warning.

  • Calls set_uart_servo_angle_array to send all 6 joint angles to the low level in one go.

4. single_arm_callback — Single-joint robotic arm angle control callback

  • Extracts the joint ID id, target angle joint, and motion time time from the ArmJoint message.

  • Validates whether the joint ID is legal (1~6); if legal, checks the angle range and clamps it; if not, prints a warning.

  • Calls set_uart_servo_angle to control a single servo to rotate to the specified angle.

​x

    def _odom_linear_move(self, goal_handle):
        '''Execute linear movement using internal odometry (dead-reckoning)'''
        goal = goal_handle.request
        distance = goal.distance
        direction = goal.direction

        linear_speed = abs(self.odom_linear_speed)
        start_x = self.odom_x
        start_y = self.odom_y

        # Validate direction
        if direction not in ('forward', 'backward', 'left', 'right'):
            self.get_logger().error(f"Unknown linear direction: {direction}")
            goal_handle.abort()
            result = MoveByOdom.Result()
            result.success = False
            result.message = f"Unknown linear direction: {direction}"
            return result

        # Ramp-down thresholds (meters)
        CLOSE_THRESHOLD = 0.1   # Below this: minimum speed
        RAMP_THRESHOLD = 0.3     # Below this: linear ramp from full to min
        MIN_SPEED = 0.07          # Minimum speed (m/s) to avoid stall

        start_time = time.time()
        while rclpy.ok():
            # Check timeout
            if time.time() - start_time > self.odom_timeout:
                self.get_logger().warn(f"Linear movement timeout ({self.odom_timeout}s)")
                goal_handle.abort()
                result = MoveByOdom.Result()
                result.success = False
                result.message = f"Movement timeout after {self.odom_timeout}s"
                return result

            # Check if goal is cancelled
            if goal_handle.is_cancel_requested:
                self.get_logger().info("Linear movement cancelled")
                goal_handle.canceled()
                result = MoveByOdom.Result()
                result.success = False
                result.message = "Movement cancelled"
                return result

            # Publish feedback using internal odometry
            dx = self.odom_x - start_x
            dy = self.odom_y - start_y
            moved = math.sqrt(dx*dx + dy*dy)

            feedback = MoveByOdom.Feedback()
            feedback.moved_distance = float(moved)
            feedback.rotated_angle = 0.0
            goal_handle.publish_feedback(feedback)

            # Check if target distance reached
            if moved >= abs(distance) - self.odom_position_tolerance:
                self.get_logger().info(
                    f"Linear movement complete! Moved {moved:.3f}m")
                goal_handle.succeed()
                result = MoveByOdom.Result()
                result.success = True
                result.message = f"Moved {direction} {moved:.3f}m"
                return result

            # --- Ramp-down: gradual deceleration when approaching target ---
            distance_to_go = abs(distance) - moved
            if distance_to_go < CLOSE_THRESHOLD:
                ramp_speed = MIN_SPEED
            elif distance_to_go < RAMP_THRESHOLD:
                ramp_speed = MIN_SPEED + (linear_speed - MIN_SPEED) * (
                    (distance_to_go - CLOSE_THRESHOLD) / (RAMP_THRESHOLD - CLOSE_THRESHOLD))
            else:
                ramp_speed = linear_speed

            # Map direction to velocity components with ramp speed
            if direction == 'forward':
                vx, vy = ramp_speed, 0.0
            elif direction == 'backward':
                vx, vy = -ramp_speed, 0.0
            elif direction == 'left':
                vx, vy = 0.0, ramp_speed
            else:  # right
                vx, vy = 0.0, -ramp_speed

            # Send velocity command
            self.car.set_car_motion(vx, vy, 0.0)
            time.sleep(0.1)

        # Should not reach here, but guard
        goal_handle.abort()
        result = MoveByOdom.Result()
        result.success = False
        result.message = "Unexpected exit from control loop"
        return result

    def Buzzercallback(self,msg: Bool):
        if not isinstance(msg, Bool): return
        if msg.data:
            for i in range(3): self.car.set_beep(1)
        else:
            for i in range(3): self.car.set_beep(0)

    def arm_callback(self, msg: ArmJoints):
        j1 = msg.joint1
        j2 = msg.joint2
        j3 = msg.joint3
        j4 = msg.joint4
        j5 = msg.joint5
        j6 = msg.joint6
        angles = [j1, j2, j3, j4, j5, j6]
        
        for i, (angle, bound) in enumerate(zip(angles, self.bounds)):
            if angle < bound[0] or angle > bound[1]:
                clamped = max(bound[0], min(angle, bound[1]))
                self.get_logger().warn(f"Arm joint {i+1} angle {angle} exceeds bounds [{bound[0]}, {bound[1]}], clamped to {clamped}")
                angles[i] = int(clamped)
        run_time = int(msg.time)
        self.car.set_uart_servo_angle_array(angle_s=angles, run_time=run_time)

    def single_arm_callback(self, msg: ArmJoint):
        jid = msg.id
        angle = msg.joint
        duration = msg.time
        
        if 1 <= jid <= len(self.bounds):
            bound = self.bounds[jid - 1]
            if angle < bound[0] or angle > bound[1]:
                clamped = max(bound[0], min(angle, bound[1]))
                self.get_logger().warn(f"Arm joint {jid} angle {angle} exceeds bounds [{bound[0]}, {bound[1]}], clamped to {clamped}")
                angle = int(clamped)
        else:
            self.get_logger().warn(f"Invalid arm joint ID: {jid}")
        
        self.get_logger().debug(f"Arm single ID:{jid}, angle:{angle}")
        self.car.set_uart_servo_angle(jid, angle, duration)
        
RobotManager User Guide
Robot Handle Control

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