raspimouse_ros2_examples

ROS 2 examples for Raspberry Pi Mouse.

ROS1 examples is here.

To run on Gazebo, click here.

<img src=https://rt-net.github.io/images/raspberry-pi-mouse/raspberry_pi_mouse.JPG width=500 />

Supported ROS 2 distributions

• Humble
• Jazzy (This branch)

Requirements

• Raspberry Pi Mouse
  • https://rt-net.jp/products/raspberrypimousev3/
  • Linux OS
    • Ubuntu server 24.04
  • Device Driver
    • rt-net/RaspberryPiMouse
  • ROS
    • Jazzy Jalisco
  • Raspberry Pi Mouse ROS 2 package
    • https://github.com/rt-net/raspimouse2
• Remote Computer (Optional)
  • ROS
    • Jazzy Jalisco
  • Raspberry Pi Mouse ROS 2 package
    • https://github.com/rt-net/raspimouse2

Installation

$ cd ~/ros2_ws/src
# Clone package
$ git clone -b $ROS_DISTRO https://github.com/rt-net/raspimouse_ros2_examples.git

# Install dependencies
$ rosdep install -r -y --from-paths . --ignore-src

# Build & Install
$ cd ~/ros2_ws
$ colcon build --symlink-install
$ source ~/ros2_ws/install/setup.bash

License

This repository is licensed under the Apache 2.0, see LICENSE for details.

How To Use Examples

• joystick_control
• object_tracking
• line_follower
• camera_line_follower
• SLAM
• direction_controller

joystick_control

This is an example to use joystick controller to control a Raspberry Pi Mouse.

Requirements

• Joystick Controller
  • Logicool Wireless Gamepad F710
  • SONY DUALSHOCK 3

How to use

Launch nodes with the following command:

# Use F710
$ ros2 launch raspimouse_ros2_examples teleop_joy.launch.py joydev:="/dev/input/js0" joyconfig:=f710 mouse:=true

# Use DUALSHOCK 3
$ ros2 launch raspimouse_ros2_examples teleop_joy.launch.py joydev:="/dev/input/js0" joyconfig:=dualshock3 mouse:=true

# Control from remote computer
## on RaspberryPiMouse
$ ros2 run raspimouse raspimouse
## on remote computer
$ ros2 launch raspimouse_ros2_examples teleop_joy.launch.py mouse:=false

This picture shows the default key configuration.

To use Logicool Wireless Gamepad F710, set the input mode to D (DirectInput Mode).

Configure

Key assignments can be edited with key numbers in ./config/joy_f710.yml or ./config/joy_dualshock3.yml.

button_shutdown_1       : 8
button_shutdown_2       : 9

button_motor_off        : 8
button_motor_on         : 9

button_cmd_enable       : 4

Videos

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object_tracking

<img src=https://rt-net.github.io/images/raspberry-pi-mouse/object_tracking.JPG width=500 />

This is an example to use RGB camera images and OpenCV library for object tracking.

Requirements

• Web camera
  • Logicool HD WEBCAM C310N
• Camera mount
  • Raspberry Pi Mouse Option kit No.4 [Webcam mount]
• Orange ball（Optional）
  • Soft Ball (Orange)
• Software
  • OpenCV
  • v4l-utils

Installation

Install a camera mount and a web camera to Raspberry Pi Mouse, then connect the camera to the Raspberry Pi．

How to use

Turn off automatic adjustment parameters of a camera (auto focus, auto while balance, etc.) with the following command:

$ cd ~/ros2_ws/src/raspimouse_ros2_examples/config
$ ./configure_camera.bash

Then, launch nodes with the following command:

$ ros2 launch raspimouse_ros2_examples object_tracking.launch.py video_device:=/dev/video0

This sample publishes two topics: camera/color/image_raw for the camera image and result_image for the object detection image. These images can be viewed with RViz or rqt_image_view.

Viewing an image may cause the node to behave unstable and not publish cmd_vel or image topics.

<img src=https://rt-net.github.io/images/raspberry-pi-mouse/object_tracking_ros2.png width=500 />

Configure

Edit ./src/object_tracking_component.cpp to change a color of tracking target.

If the object detection accuracy is poor, adjust the camera exposure and parameters in the function

void Tracker::tracking(const cv::Mat & input_frame, cv::Mat & result_frame)
{
  cv::inRange(hsv, cv::Scalar(9, 100, 100), cv::Scalar(29, 255, 255), extracted_bin);  // Orange
  // cv::inRange(hsv, cv::Scalar(60, 100, 100), cv::Scalar(80, 255, 255), extracted_bin);  // Green
  // cv::inRange(hsv, cv::Scalar(100, 100, 100), cv::Scalar(120, 255, 255), extracted_bin);  // Blue

Videos

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line_follower

<img src=https://rt-net.github.io/images/raspberry-pi-mouse/mouse_with_line_trace_sensor.JPG width=500 />

This is an example for line following.

Requirements

• Line following sensor
  • Raspberry Pi Mouse Option kit No.3 [Line follower]
• Field and lines for following (Optional)

Installation

Install a line following sensor unit to Raspberry Pi Mouse.

How to use

Launch nodes with the following command:

$ ros2 launch raspimouse_ros2_examples line_follower.launch.py

Next, place Raspberry Pi Mouse on a field and press SW2 to sample sensor values on the field.

<img src=https://rt-net.github.io/images/raspberry-pi-mouse/field_calibration.JPG width=500 />

Then, place Raspberry Pi Mouse to detect a line and press SW1 to sample sensor values on the line.

<img src=https://rt-net.github.io/images/raspberry-pi-mouse/line_calibration.JPG width=500 />

Last, place Raspberry Pi Mouse on the line and press SW0 to start line following.

<img src=https://rt-net.github.io/images/raspberry-pi-mouse/start_trace.JPG width=500 />

Press SW0 again to stop the following.

Configure

Edit ./src/line_follower_component.cpp to change a velocity command.

void Follower::publish_cmdvel_for_line_following(void)
{
  const double VEL_LINEAR_X = 0.08;  // m/s
  const double VEL_ANGULAR_Z = 0.8;  // rad/s
  const double LOW_VEL_ANGULAR_Z = 0.5;  // rad/s

Videos

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camera_line_follower

<img src=https://rt-net.github.io/images/raspberry-pi-mouse/mouse_camera_line_trace_2.png width=500 />

This is an example for line following by RGB camera.

Requirements

• Web camera
  • Logicool HD WEBCAM C310N
• Camera mount
  • Raspberry Pi Mouse Option kit No.4 [Webcam mount]

Installation

Install a camera mount and a web camera to Raspberry Pi Mouse, then connect the camera to the Raspberry Pi．

How to use

Then, launch nodes with the following command:

$ ros2 launch raspimouse_ros2_examples camera_line_follower.launch.py video_device:=/dev/video0

Place Raspberry Pi Mouse on the line and press SW2 to start line following.

Press SW0 to stop the following.

This sample publishes two topics: camera/color/image_raw for the camera image and result_image for the object detection image. These images can be viewed with RViz or rqt_image_view.

Viewing an image may cause the node to behave unstable and not publish cmd_vel or image topics.

If the line detection accuracy is poor, please adjust the camera’s exposure and white balance.

<img src=https://rt-net.github.io/images/raspberry-pi-mouse/camera_line_trace.png width=500 />

Parameters

• max_brightness
  • Type: int
  • Default: 90
  • Maximum threshold value for image binarisation.
• min_brightness
  • Type: int
  • Default: 0
  • Minimum threshold value for image binarisation.
• max_linear_vel
  • Type: double
  • Default: 0.05
  • Maximum linear velocity.
• max_angular_vel
  • Type: double
  • Default: 0.8
  • Maximum angular velocity.
• area_threthold
  • Type: double
  • Default: 0.20
  • Threshold value of the area of the line to start following.

ros2 param set /camera_follower max_brightness 80

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SLAM

<img src=https://rt-net.github.io/images/raspberry-pi-mouse/slam_toolbox_ros2.png width=500 />

SLAM and Navigation examples for Raspberry Pi Mouse is here.

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direction_controller

<img src=https://www.rt-shop.jp/images/RT/RT-USB-9axisIMU.png width=200 /> <img src=https://www.rt-shop.jp/images/RT/%E8%A3%BD%E5%93%81%E5%86%99%E7%9C%9F.JPG height=200>

This is an example to use an IMU sensor for direction control.

Requirements

• USB output 9 degrees IMU sensor module
• LiDAR Mount
• RT-USB-9axisIMU ROS Package.
  • https://github.com/rt-net/rt_usb_9axisimu_driver

Installation

Install the IMU sensor module to the LiDAR mount.

<img src=https://rt-net.github.io/images/raspberry-pi-mouse/mouse_with_imu_2.JPG width=500 />

Install the LiDAR mount to the Raspberry Pi Mouse.

<img src=https://rt-net.github.io/images/raspberry-pi-mouse/mouse_with_imu_1.JPG width=500 />

How to use

Launch nodes on Raspberry Pi Mouse with the following command:

$ ros2 launch raspimouse_ros2_examples direction_controller.launch.py

Then, press SW0 ~ SW2 to change the control mode as following,

• SW0: Calibrate the gyroscope bias and reset a heading angle of Raspberry Pi Mouse to 0 rad.
• SW1: Start a direction control to keep the heading angle to 0 rad.
  • Press SW0 ~ SW2 or tilt the body to sideways to finish the control.
• SW2: Start a direction control to change the heading angle to -π ~ π rad.
  • Press SW0 ~ SW2 or tilt the body to sideways to finish the control.

Troubleshooting

The IMU might not be connected correctly. Reconnect the USB cable several times and re-execute the above command.

Configure

Set parameters to configure gains of a PID controller for the direction control.

$ ros2 param set /direction_controller p_gain 10.0
Set parameter successful

$ ros2 param set /direction_controller i_gain 0.5
Set parameter successful

$ ros2 param set /direction_controller d_gain 0.0
Set parameter successful

Parameters

• p_gain
  • Proportional gain of a PID controller for the direction control
  • default: 10.0, min:0.0, max:30.0
  • type: double
• i_gain
  • Integral gain of a PID controller for the direction control
  • default: 0.0, min:0.0, max:5.0
  • type: double
• d_gain
  • Derivative gain of a PID controller for the direction control
  • default: 20.0, min:0.0, max:30.0
  • type: double
• target_angle
  • Target angle for the SW1 control mode.
  • default: 0.0, min:-π, max:+π
  • type: double

Publish topics

• heading_angle
  • Heading angle of the robot that calculated from the IMU module sensor values.
  • type: std_msgs/Float64

Videos

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