Xicro Package

Xicro is ROS2 package for microcontroller interface originally made for replacing micro-ROS. Xicro allows the developers to use the generated libraries for the microcontrollers as well as auto-generated node that intrepreter information from/to the microcontrollers via UART. In this documentation, Xicro is used for transmit navigation message from microcontroller to ROS2 including Odometry and Imu measurement. Also from ROS2 to microcontroller including Twist for robot velocity command.

Create custom message for microcontroller interface

In the xicro_interfaces/msg directory, create 3 new files for navigation message including Odometry.msg, Imu.msg and DiffDriveTwist.msg then write below codes to each file to create custom message.

Type: xicro_interfaces/msg/Odometry

xicro_interfaces/Pose pose
xicro_interfaces/Twist twist

Type: xicro_interfaces/msg/Imu

xicro_interfaces/Quaternion orientation
xicro_interfaces/Vector3 angular_velocity
xicro_interfaces/Vector3 linear_acceleration

Type: xicro_interfaces/msg/DiffDriveTwist

float32 linear
float32 angular

Setup parameter in setup_xicro.yaml

In xicro yaml file, Set Baudrate to 576000 for a highest transmission rate of Xicro, then declare topics for all navigation messages in Setup_Publisher and Setup_Subscriber. Microcontroller port is set to /dev/ttyACM0 from Hardware setup.

Idmcu: 3
Namespace: "sub_N_pub"
Port: "/dev/ttyACM0"
generate_library_Path: "xicro/libraries"
Baudrate: 576000
Setup_Publisher:  [ [1,"nav_stm32","xicro_interfaces/Odometry.msg"], [2,"imu_stm32","xicro_interfaces/Imu.msg"] ]
Setup_Subscriber: [ [1,"cmd_vel_stm32","xicro_interfaces/DiffDriveTwist.msg"] ]
Setup_Srv_client: []

Create xicro library for microcontroller

After yaml config, The stm32 library will be generated based on setup_xicro.yaml when run the following command:

ros2 run xicro_pkg generate_library.py stm32 stm32h7xx_hal.h

Stm32 library will be generated in ~/xicro/libraries. So you need to bring this .h and .cpp to your stm32 project.

Create xicro node

The node will be generated based on setup_xicro.yaml when run the following command:

ros2 run xicro_pkg generate_xicro_node.py stm32

Caution

After running the command, VScode will display the node that was created. Delete line 11 !Delete this line to verify the code. and save it The entry point is add auto by command.

Create navigation message publisher node

This node is not an native xicro node. It’s made in xicro_pkg/scripts just to create interface node between microcontroller and ROS2 in order to publish and subscribe navigation message. These are all interface topics and files in nav_msg_publisher node:

• Navigation Interface

  • Publish Topic

    • /imu/data (sensor_msgs/msg/Imu)

    • /wheel/odometry (nav_msgs/msg/Odometry)

  • Subscribe Topic

    • /cmd_vel (geometry_msgs/msg/Twist)

• Microcontroller Interface

  • Publish Topic

    • /cmd_vel_stm32 (xicro_interfaces/msg/DiffDriveTwist)

  • Subscribe Topic

    • /imu_stm32 (xicro_interfaces/msg/Imu)

    • /nav_stm32 (xicro_interfaces/msg/Odometry)

• Imu Calibration Interface

  • Yaml file

    • calibration/config/sensor_properties.yaml

In nav_msg_publisher.py, create yaml file interface to load imu sensor properties from calibration-package:

# Load Imu calibration value from Yaml file
calibration_gen_path = get_package_share_directory('calibration')
path = os.path.join(calibration_gen_path,'config','sensor_properties.yaml')
with open(path) as f:
    self.properties = yaml.load(f, Loader=yaml.loader.UnsafeLoader)

print("Load IMU calibration file: 'sensor_properties.yaml' in share calibration package Success...")

# Set imu calibration value from yaml file
self.lin_acc_x_bias = self.properties['mean'][0]
self.lin_acc_y_bias = self.properties['mean'][1]
self.lin_acc_z_bias = self.properties['mean'][2]
self.ang_vel_x_bias = self.properties['mean'][3]
self.ang_vel_y_bias = self.properties['mean'][4]
self.ang_vel_z_bias = self.properties['mean'][5]
# Set imu variance from yaml file
self.lin_acc_x_var = self.properties['covariance'][0]
self.lin_acc_y_var = self.properties['covariance'][7]
self.lin_acc_z_var = self.properties['covariance'][14]
self.ang_vel_x_var = self.properties['covariance'][21]
self.ang_vel_y_var = self.properties['covariance'][28]
self.ang_vel_z_var = self.properties['covariance'][35]

After receiving imu message from microcontroller, create callback_imu_stm32 to calibrate imu raw data with sensor properties and make standard ros2 imu message (sensor_msgs/msg/Imu)

def callback_imu_stm32(self,msg:imu):
    # Assign value from imu msg to node internal value
    self.imu_orientation = msg.orientation
    self.imu_angular_velocity = msg.angular_velocity
    self.imu_linear_acceleration = msg.linear_acceleration
    # Publish Imu to navigation (with same rate of controller)
    imu_msg = Imu()
    imu_msg.header.frame_id="base_footprint"
    now = self.get_clock().now()
    imu_msg.header.stamp = now.to_msg()

    # Linear acceleration
    imu_msg.linear_acceleration.x = self.imu_linear_acceleration.x - self.lin_acc_x_bias
    imu_msg.linear_acceleration.y = self.imu_linear_acceleration.y - self.lin_acc_y_bias
    imu_msg.linear_acceleration.z = self.imu_linear_acceleration.z - self.lin_acc_z_bias

    # Angular velocity
    imu_msg.angular_velocity.x = self.imu_angular_velocity.x - self.ang_vel_x_bias
    imu_msg.angular_velocity.y = self.imu_angular_velocity.y - self.ang_vel_y_bias
    imu_msg.angular_velocity.z = self.imu_angular_velocity.z - self.ang_vel_z_bias

    # Orientation
    imu_msg.orientation.x = self.imu_orientation.x
    imu_msg.orientation.y = self.imu_orientation.y
    imu_msg.orientation.z = self.imu_orientation.z
    imu_msg.orientation.w = self.imu_orientation.w

    imu_msg.linear_acceleration_covariance =[self.lin_acc_x_var,0.0,0.0,0.0,self.lin_acc_y_var,0.0,0.0,0.0,self.lin_acc_z_var]
    imu_msg.angular_velocity_covariance=[self.ang_vel_x_var,0.0,0.0,0.0,self.ang_vel_y_var,0.0,0.0,0.0,self.ang_vel_z_var]
    imu_msg.orientation_covariance=[0.000000001,0.0,0.0,0.0,0.000000001,0.0,0.0,0.0,0.000000001]

    self.imu_publisher.publish(imu_msg)

After receiving odometry message from microcontroller, create callback_nav_stm32 to fill original data with pose covariance and twist covariance to make standard odometry message (nav_msgs/msg/odometry)

def callback_nav_stm32(self,msg:odom):
    # Assign value from odom msg to node internal value
    self.robot_pose = msg.pose
    self.robot_twist = msg.twist
    # Publish Odometry to navigation (with same rate of controller)
    odom_msg = Odometry()
    odom_msg.header.frame_id="odom"
    now = self.get_clock().now()
    odom_msg.header.stamp = now.to_msg()
    odom_msg.child_frame_id="base_footprint"

    # PoseWithCovariance
    odom_msg.pose.pose.position.x = self.robot_pose.position.x
    odom_msg.pose.pose.position.y = self.robot_pose.position.y
    odom_msg.pose.pose.position.z = self.robot_pose.position.z
    odom_msg.pose.pose.orientation.x = self.robot_pose.orientation.x
    odom_msg.pose.pose.orientation.y = self.robot_pose.orientation.y
    odom_msg.pose.pose.orientation.z = self.robot_pose.orientation.z
    odom_msg.pose.pose.orientation.w = self.robot_pose.orientation.w

    odom_msg.pose.covariance = [0.1, 0.0, 0.0, 0.0, 0.0, 0.0,
                                0.0, 0.1, 0.0, 0.0, 0.0, 0.0,
                                0.0, 0.0, 0.000000001, 0.0, 0.0, 0.0,
                                0.0, 0.0, 0.0, 0.000000001, 0.0, 0.0,
                                0.0, 0.0, 0.0, 0.0, 0.000000001, 0.0,
                                0.0, 0.0, 0.0, 0.0, 0.0, 0.1,]
    # TwistWithCovariance
    odom_msg.twist.twist.linear.x = self.robot_twist.linear.x
    odom_msg.twist.twist.linear.y = self.robot_twist.linear.y
    odom_msg.twist.twist.linear.z = self.robot_twist.linear.z
    odom_msg.twist.twist.angular.x = self.robot_twist.angular.x
    odom_msg.twist.twist.angular.y = self.robot_twist.angular.y
    odom_msg.twist.twist.angular.z = self.robot_twist.angular.z

    odom_msg.twist.covariance = [0.00477649365, 0.0, 0.0, 0.0, 0.0, 0.0,
                                0.0, 0.000000001, 0.0, 0.0, 0.0, 0.0,
                                0.0, 0.0, 0.000000001, 0.0, 0.0, 0.0,
                                0.0, 0.0, 0.0, 0.000000001, 0.0, 0.0,
                                0.0, 0.0, 0.0, 0.0, 0.000000001, 0.0,
                                0.0, 0.0, 0.0, 0.0, 0.0, 0.0530721471,]

    self.wheel_odometry_publisher.publish(odom_msg)

When navigation node send command velocity to control mobile robot, cmd_vel_callback will extract only linear velocity of x and angular velocity of z to make custom twist message then sent to microcontroller via Xicro.

def cmd_vel_callback(self,msg:Twist):
    # Assign value from twist msg to node internal value
    self.robot_cmd_vel.linear = msg.linear.x
    self.robot_cmd_vel.angular = msg.angular.z
    # Publish DiffDriveTwist to robot (with same rate of command velocity)
    twist_msg = DiffDriveTwist()
    twist_msg = self.robot_cmd_vel
    self.robot_twist_publisher.publish(twist_msg)