Raspberry Pi Light Trace System - Embedded OS System
Published:
Project Overview
I led a groundbreaking project centered on developing a Light Tracker system that emulates the natural behavior of sunflowers. This innovative project aimed to seamlessly integrate computer vision, servo motors, and user-friendly controls to create a system capable of accurately tracking moving light sources. The Light Tracker holds immense potential for applications in solar energy optimization, smart agriculture, and interactive art installations.
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Design and Implementation
The project encompassed two distinct approaches to light tracking:
- Camera-based Tracking:
- Utilized OpenCV library to detect the brightest point in captured images.
- Employed servo motors to adjust the panel’s orientation, keeping the light source centered.
- Photoresistor-based Tracking:
- Implemented four photoresistors to detect changes in light luminosity.
- Calculated the light source’s position based on the relative luminosity values.
The system combined mechanical and electronic components with Python programming on a Raspberry Pi to create a sophisticated light-tracking solution. Advanced techniques such as Gaussian filtering, edge detection, and proportional control were employed to enhance tracking accuracy and responsiveness.
User Interface and Interaction
- Developed an intuitive three-level GUI using piTFT touch control.
- Provided users with options to select the tracking method and display real-time system information.
Hardware Integration and Optimization
- Successfully integrated PCF8591 ADC-DAC modules and TCA9548A I2C multiplexer for photoresistor-based tracking.
- Optimized servo motor control using PWM signals for smooth and precise panel movement.
- Overcame challenges related to I2C bus communication and component compatibility.
Project Management and Collaboration
As the project lead, I effectively coordinated tasks, managed timelines, and fostered a collaborative environment within the team. Regular meetings were conducted to discuss progress, address challenges, and ensure alignment with project goals. I actively contributed to hardware assembly, software development, and system integration.
Skill Enhancement
This project significantly expanded my skill set, strengthening my expertise in computer vision, embedded systems, and hardware-software integration. I gained proficiency in OpenCV, Raspberry Pi programming, servo motor control, and I2C communication protocols. Additionally, the project honed my problem-solving abilities and reinforced the importance of effective project management and teamwork.
Work Distribution
- Winchester Zhang (sz442): Circuit design, Software development (Photoresistor Mode), System testing
- Yuning Xia (yx546): Software Development (Light Mode), Robot Motion System Development, Web Development
- Suhan Shi (ss3389): Software Development (Photoresistor Mode), PyGame Interface Design, System Testing