Strawberry Picking Robot Arm

This project implements an autonomous robot arm capable of perceiving and picking strawberries along a ridgeline using a Raspberry Pi and computer vision.

Overview

The system combines visual perception with a robotic arm to locate and pick strawberries in a structured environment. It uses ROS 2 Jazzy for coordination, Docker for containerized development, and a combination of Raspberry Pi and Arduino for hardware control.

Hardware Overview

Top	Front	Inside

Demo Videos

Not damaged, Successful Pick	Not damaged, Partially Successful Pick	Not damaged, Unsuccessful Pick	Damaged, Successful Pick

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Requirements

Hardware

• Raspberry Pi 5
• 2× Pi Camera Module 3 (1 wide-angle, 1 normal)
• Arduino Uno
• 5-DOF Robotic Arm

Software

• RaspberryPi OS
• ROS 2 Jazzy (inside the dev container)
• Git Bash or similar terminal

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Installation

Prerequisites

• Visual Studio Code
• Dev Containers extension
• Docker installed and running on your system

Steps

1. Clone the repository:

   git clone https://github.com/ianueph/strawberry-picking-rpi.git
   cd strawberry-picking-rpi

2. Open the project folder in VS Code.

3. When prompted by VS Code, "Reopen in Container".

4. The container will build and install all dependencies automatically via:

   • installations.sh
   • postCreateCommand.sh

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Deployment

After setup and connecting all hardware:

1. Upload YOLO Model Weights

   Before launching the robot system, ensure the required YOLOv8 model weights are available. Place the following files in the specified directory:

   src/
   └── yolo_ros/
       ├── ...
       ├── yolo_bringup/
       │   ├── launch/
       │   │   ├── strawberry-object-tracking.pt
       │   │   ├── strawberry-image-class.pt
       │   │   └── ...
       │   └── ...
       ├── yolo_msgs/
       │   └── ...
       ├── yolo_ros/
       │   └── ...
       └── ...

2. Grant access to the Arduino serial device:

   sudo chmod 666 /dev/ttyACM0

3. Launch the robot system:

   ros2 launch sprpi_arm_bringup main_launch.launch.py

Note: Ensure you have X11 forwarding set up properly if running GUI apps like RViz2. This is handled via mounted volumes and environment variables in devcontainer.json.

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Notes

• Ensure both Pi Cameras are connected and recognized by the Raspberry Pi.
• The Arduino should be flashed with the correct firmware for arm control.
• This project assumes basic familiarity with ROS 2, Linux, and Docker.

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