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RDK X3 Robot📖
01. About RDK-X3-Robot
1. Instructions
  • 1. Introduction
  • 2. FAQ
  • 3. Battery and charger use precautions
  • 4.TF card expand capacity
2. Common problem analysis
02. Assembly video
  • Part1-Install Motor
  • Part2-Install Battert Fixing Column
  • Part3-Install Motor Coupling
  • Part4-Install Mecanum wheel
  • Part5-Install Expansion Board
  • Part6-Wiring Show
  • Part7-Install Main Control Board
  • Part8-Install Car Top Plate and Antenna
  • Part9-Install OLED Screen
  • Part10-Install Depth Camera(Optional)
  • Part11-Install OLED Screen
  • Part12-Install HD Camera
  • Part13-Install Top Plate
  • Part14-Install Right Side Plate
  • Part15-Motor Wiring Show
  • Part16-lnstall Car Body
  • Part17-Install Battery
  • Part18-Install Lidar
03. Remote control tutorial
  • 1. The phone APP remote tutorial
  • 2. USB wireless controller remote tutorial
04. ROS functional tutorial
  • 1. Introduction of extension board
  • 2. Set up STM32 development environment
  • 3. Key control buzzer sound
  • 4. FreeRTOS application
  • 5. Serial communication
  • 6. SBUS model remote control
  • 7. CAN bus communication
  • 8. RGB color light strip
  • 9. Timer interrupt control PWM servo
  • 10. Control serial steering gear
  • 11. Nine-axis attitude sensor to obtain data
  • 12. Control motor forward and reverse
  • 13. The timer captures encoder data
  • 14. Theory of robot kinematics analysis
  • 15. PID control robot motion
05. Basic control tutorial
  • 1. Update the firmware of the expansion module
  • 2. Install the Python driver library
  • 3. Set the type of bottom car
  • 4. Open and close the APP program control
  • 5. Turn hotspot mode on and off
  • 6. The buzzer blows
  • 7. Control the motor forward and reverse
  • 8. Control robot movement
  • 9. OLED display
  • 10. Control fan and lamp effect
06. Development environment setup
  • 1. Virtual Machine
  • 2. Linux Basics
  • 3. Remote connection
  • 4. Multi-computer communication configuration
  • 5. Bind the device ID
  • 6. Image installation and backup
07. 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
08. Robot chassis control
  • 1. PID algorithm theory
  • 2. Robot information release
  • 3. Robot control
  • 4. Robot state estimation
  • 5. Robot calibration
  • 6. Robot trajectory tracking
  • 7. URDF model
09. Lidar courses
  • 1. Introduction and use of lidar
  • 2. Lidar obstacle avoidance
  • 3. Lidar following
  • 4. Lidar guard
  • 5. Patrol
  • 6. gmapping algorithm
  • 7. cartographer algorithm
  • 8. Navigation and obstacle avoidance
  • 9. App mapping and navigation
10. OpenCV courses
  • 1. Introduction to OpenCV
  • 2. OpenCV geometric transformation
  • 3. OpenCV image processing
  • 4. OpenCV image beautification
  • 5. Qr code creation and identification
11. MIPI camera course
  • 1. Camera driver
  • 2. Adjust the color HSV value
  • 3. Color recognition
  • 4. Color tracking
  • 5. Color follow
  • 6. Qr code command
  • 7. Face detection
  • 8. Object detection
  • 9. Visual Inspection -OpenCV
  • 10. Visual inspection - Deep learning
  • 11. Human tracking
  • 12. Gesture control
12. Depth Camera courses
  • 1. Use depth camera
  • 2. Calibration of camera internal reference
  • 3. ROS+OpenCV Foundation
  • 4. AR vision
  • 5. Color tracking
  • 6. Object tracking
13. Multi vehicle control
  • 1. Multi-vehicle synchronous control
  • 2. Multi-vehicle navigation
Remote login control
  • 1. VNC and SSH remote login
  • 2. Jupyter lab login and case code running
Download
  • RemoteCtrl_APP(iOS/Android))
  • Mapping_APP(iOS_Android)
  • Code
  • System File
  • VM_File
  • Manual
  • Software_File
  • Hardware_File
  • ROS2_Basic_VM
Download ZIP

Welcome to RDK X3 Robot repository

15. ROS2 time related API

15.ROS2 time related API

 

1. Introduction to Time-Related APIs

ROS2's time-related APIs include Rate, Time, Duration, and operations on Time and Duration. These are explained below.

  • First, create a function package to store the relevant program files.
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ros2 pkg create learning_time --build-type ament_python --dependencies rclpy

2. create_rate

ROS2 also provides the create_rate function, a tool for controlling loop execution frequency. Its core function is to periodically execute a section of code at a fixed frequency. Rate ensures the stability of the loop execution frequency by controlling the "sleep time" of the loop. Remember that Rate should generally not be used directly in the main thread, as doing so will permanently block callback events. It is generally only used in programs with multi-threaded callbacks or in child threads.

How it works:

  1. Records the start time of each loop;
  2. Executes the code within the loop;
  3. Calculates the difference between the current loop's actual duration and the target interval;
  4. Automatically sleeps for the corresponding difference, ensuring that the interval from the start of one loop to the start of the next strictly equals the target interval (e.g., 100 milliseconds).

While both Rate and Timer can implement periodic execution, their application scenarios differ:

FeaturesRateTimer
ImplementationBased on active sleep within a loop (blocking the current thread)Based on callback functions (non-blocking, triggered by the ROS 2 event loop)
Applicable ScenariosSuitable for loops that need to execute at a fixed frequency within the same thread (such as main control logic)Suitable for periodic tasks that need to execute asynchronously (without blocking the main thread)
FlexibilityDirect control flow within the loop (such as break exit)Callback execution must be controlled using flags or other methods
  • The following is a basic usage of Rate to implement a loop that executes twice per second:
  • Create a new file in the function package called rate_demo.py
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import rclpy
from rclpy.node import Node
import threading
​
class RateExampleNode(Node):
    def __init__(self):
        super().__init__("rate_example_node")
        self.get_logger().info("Rate 示例节点启动")
​
    def run_loop(self):
        # Use the node's create_rate() to create a 2Hz Rate
        rate = self.create_rate(2)
        
        count = 0
        try:
            while rclpy.ok():
                self.get_logger().info(f"循环执行 {count} 次")
                count += 1
                rate.sleep()  # Sleep until the next cycle (0.5 seconds)
        except KeyboardInterrupt:
            self.get_logger().info("循环被中断")
​
def main(args=None):
    rclpy.init(args=args)
    node = RateExampleNode()
    
    # Create a thread run loop (to avoid blocking the main thread)
    loop_thread = threading.Thread(target=node.run_loop)
    loop_thread.start()
    
    # The main thread executes spin to keep the ROS 2 node running
    try:
        rclpy.spin(node)
    except KeyboardInterrupt:
        pass
    finally:
        loop_thread.join()  # Waiting for the thread to end
        node.destroy_node()
        rclpy.shutdown()
​
if __name__ == "__main__":
    main()
    

 

  • Configure the corresponding setup.py configuration file and add it in console_scripts
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'rate_demo=learning_time.rate_demo:main'

image-20250905155834618

 

  • Compile feature package
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colcon build --packages-select learning_time

image-20250905155916058

 

  • Refresh the workspace environment and run the node
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 source ./install/setup.bash
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ros2 run learning_time rate_demo

image-20250905155949678

 

3. Timer Application

  • Timer is used to create a timer that triggers periodic tasks.
  • Example: Create two timers: one that prints the execution count every 1 second, and one that prints the current time every 0.5 seconds.
  • Create a new program file called Timer_demo.py
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import rclpy
from rclpy.node import Node
​
class TimerDemoNode(Node):
    def __init__(self):
        super().__init__('timer_demo_node')
        
        # Counter, used to demonstrate the number of timer executions
        self.counter = 0
        
        # Create a timer: execute the callback function every 1 second
        self.timer = self.create_timer(1.0, self.timer_callback)
        
        # Create a faster timer: execute every 0.5 seconds
        self.fast_timer = self.create_timer(0.5, self.fast_timer_callback)
        
        self.get_logger().info("定时器节点已启动")
​
    def timer_callback(self):
        """1 second timer callback function"""
        self.counter += 1
        current_time = self.get_clock().now()
        
        # Print the current time and counter value
        self.get_logger().info(
            f"[1秒定时器] 第 {self.counter} 次执行,当前时间: {current_time.seconds_nanoseconds()}"
        )
​
    def fast_timer_callback(self):
        """0.5 second timer callback function"""
        # Print the current timestamp (nanoseconds)
        self.get_logger().info(
            f"[0.5秒定时器] 当前时间戳: {self.get_clock().now().nanoseconds}"
        )
​
def main(args=None):
    # Initializing ROS 2
    rclpy.init(args=args)
    
    # Creating a Node
    node = TimerDemoNode()
    
    # Running a Node
    rclpy.spin(node)
    
    # Shut down ROS 2
    node.destroy_node()
    rclpy.shutdown()
​
if __name__ == '__main__':
    main()
​
  • Configure the corresponding setup.py configuration file and add it in console_scripts
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'Timer_demo=learning_time.Timer_demo:main'

image-20250905160115901

 

  • Compile function package
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colcon build --packages-select learning_time

image-20250905155916058

 

  • Refresh the workspace environment and run the node
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source ./install/setup.bash
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ros2 run learning_time Timer_demo

image-20250905160239330

  • It can be seen that the timer is triggered according to the set timing, and the corresponding log information is printed in each callback function

 

4. Get the Current Time with get_clock

  • The get_clock function can be used to obtain a clock object and then use the () method to get the current time.
  • Create a new program file, get_clock_demo.py, and fill it with the following example program:
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import rclpy
from rclpy.node import Node
from rclpy.time import Time
​
class TimeExampleNode(Node):
    def __init__(self):
        super().__init__("time_example_node")
        
        # Get the node's clock object (the system clock is used by default)
        self.clock = self.get_clock()
        
        # Get the current time (return a Time object)
        current_time = self.clock.now()
        self.get_logger().info(f"当前时间:{current_time}")
​
def main(args=None):
    rclpy.init(args=args)
    node = TimeExampleNode()
    rclpy.spin_once(node)  # Run a node once
    node.destroy_node()
    rclpy.shutdown()
​
if __name__ == "__main__":
    main()
  • Configure the corresponding setup.py configuration file and add it in console_scripts
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'get_clock_demo=learning_time.get_clock_demo:main'

image-20250905160541502

 

  • Compile feature package
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colcon build --packages-select learning_time

image-20250905155916058

  • Refresh the workspace environment and run the node
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 source ./install/setup.bash
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ros2 run learning_time get_clock_demo

image-20250905160631573

 

5. Time and Duration

  • The Time class in ROS represents a specific time point (e.g., "2023-10-01 12:00:00"), typically used to mark the moment an event occurred.
  • The Duration class represents an interval between two time points (e.g., "5 seconds"), used to calculate time differences or delays.
  • Example: Time and Duration Application
  • Create a new program file, TimeDuration_demo.py.
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import rclpy
from rclpy.time import Time
from rclpy.duration import Duration
​
def main():
    rclpy.init()
    node = rclpy.create_node("time_opt_node")
   
    # How to use the time class to create 'time points and moments'
    time1 = Time(seconds=10)
    time2 = Time(seconds=4)
    # How to use the Duration class to create a 'duration, a period of time'
    duration1 = Duration(seconds=3)
    duration2 = Duration(seconds=5)
          
    # Moments can be compared
    node.get_logger().info("time1 >= time2 ? %d" % (time1 >= time2))
    node.get_logger().info("time1 < time2 ? %d" % (time1 < time2))
    
    # Time periods and times can be mathematically operated
    t3 = time1 + duration1
    t4 = time1 - time2    
    t5 = time1 - duration1
​
    node.get_logger().info("t3 = %d" % t3.nanoseconds)
    node.get_logger().info("t4 = %d" % t4.nanoseconds)
    node.get_logger().info("t5 = %d" % t5.nanoseconds)
​
    # Time periods can be compared
    node.get_logger().info("-" * 80)
    node.get_logger().info("duration1 >= duration2 ? %d" % (duration1 >= duration2))
    node.get_logger().info("duration1 < duration2 ? %d" % (duration1 < duration2))
​
    rclpy.shutdown()
​
if __name__ == "__main__":
    main()
  • Configure the corresponding setup.py configuration file and add it in console_scripts
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'TimeDuration_demo=learning_time.TimeDuration_demo:main'

image-20250905160751388

 

  • Compile feature package
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colcon build --packages-select learning_time

image-20250905155916058

 

  • Refresh the workspace environment and run the node
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 source ./install/setup.bash
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ros2 run learning_time TimeDuration_demo

image-20250905160840013

  • This example proves that mathematical operations can be performed on time points and time periods, allowing us to flexibly query and operate on data with different timestamps.

 

 

 

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