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

• Foxy
• Humble (This branch)

Requirements

• Raspberry Pi Mouse
  • https://rt-net.jp/products/raspberrypimousev3/
  • Linux OS
    • Ubuntu server 22.04
    • https://ubuntu.com/download/raspberry-pi
  • Device Driver
    • rt-net/RaspberryPiMouse
  • ROS
    • Humble Hawksbill
  • Raspberry Pi Mouse ROS 2 package
    • https://github.com/rt-net/raspimouse2
• Remote Computer (Optional)
  • ROS
    • Humble Hawksbill
  • Raspberry Pi Mouse ROS 2 package
    • https://github.com/rt-net/raspimouse2

Installation

$ cd ~/ros2_ws/src
# Clone package
$ git clone -b $ROS_DISTRO-devel 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.

<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-net.jp/wp-content/uploads/2018/02/img-usb9s_01.png width=500 />

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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Changelog for package raspimouse_ros2_examples

2.2.1 (2024-08-28)

• サービスクライアントでexecutorを使用しない (#59)
• SubscriberとService Clientに別々のcallback_groupを設定 (#58)
• Contributors: ShotaAk, YusukeKato

2.2.0 (2024-03-05)

• READMEにSLAM&Navigationパッケージの案内を追加 (#53)
• Camera_FollowerクラスをCameraFollowerに変更 (#52)
• Update camera line follower: Set motor power with switch input. Add area_threthold param. (#51)
• Add velocity parameters for camera_line_follower (#50)
• カメラライントレースを修正 (#49)
• Change threthold of line detection
• Add usb_cam dependency (#48)
• RGBカメラによるライントレースの実装 (#47)
• リリースのためにCHANGELOG.rstとpackage.xmlを更新 (#45)
• Contributors: Shota Aoki, ShotaAk, YusukeKato

2.1.0 (2023-11-07)

• READMEにGazeboでも実行できることを追記 (#44)
• object_trackingにおいて画像トピックをサブスクライブするように変更 (#43)
• Contributors: YusukeKato

2.0.0 (2023-08-03)

• Humble対応 (#41)
• Contributors: Shuhei Kozasa

1.0.0 (2022-07-28)

• Update map command (#38)
• Adds config file for DUALSHOCK4 (#36)
• Update README for foxy-devel (#34)
• Remove node_ prefix from launch files (#33)
• Use ament_export_targets instead of ament_export_interfaces. (#31)
• Remove dashing check from CI (#32)
• Update rviz config to show scan and graph topics (#29)
• Add descriptions to READMEs for use_pulse_counters param settings (#28)
• Use joy_linux instead of joy (#27)
• Update CI to support ROS Foxy (#26)
• Update package.xml (#25)
• Install raspimouse2 and imu packages via rosdep command (#22)
• Add rt_usb_9axisimu_driver dependency to package.xml (#21)
• Add direction control example (#18)
• Use images of rt-net/images repo. (#17)
• Add lidar example (#14)
• Turn on/off leds with joy inputs (#15)
• Update Gamepad F710 usage in README (#13)
• Use multi threads in the object tracking example to stabilize the tracking (#11)
• update video link (#12)
• Merge teleop_joy launch files into one file. (#10)
• Add line follower examples (#9)
• Add object tracking sample (#8)
• Rename launch files (#7)
• Refactoring (#6)
• Support remote control (#5)
• Add Joystic example (#4)
• Add industrial_ci test settings (#3)
• Fix teleop.launch for flake8 check (#2)
• Add github workflow (#1)
• Contributors: Daisuke Sato, Shota Aoki, Shuhei Kozasa