ESI-Curvature Modeling of Egg Trajectories

A research project on modeling the morphological effects on egg trajectories using high-speed cameras and MATLAB.

A placeholder image for the custom-designed egg rolling test rig.

This project, which I led, focused on understanding the relationship between an egg’s physical shape and its dynamic rolling behavior. Our primary goal was to create a predictive model that could eventually be used for intelligent egg sorting systems.

Methodology

  1. Experimental Setup: We designed and built a custom egg rolling test rig. This setup allowed us to release eggs from a consistent height and initial velocity, ensuring standardized data collection.
  2. Data Acquisition: Using a high-speed camera, we captured video footage of 90 different egg samples rolling on a planar surface.
  3. Data Processing: We utilized MATLAB for video processing. Key steps included:
    • Converting 3D motion into a 2D planar model.
    • Applying Kalman filtering and its extended forms to accurately track the egg’s position.
    • Extracting key dynamic features, such as trajectory path, instantaneous velocity, acceleration, and wobble patterns.
  4. Modeling and Analysis: We applied polynomial fitting to the extracted trajectories and analyzed the impact of the egg’s shape index and eccentricity on its path.

Outcomes & Impact

The project was successfully approved at the university level and is currently being prepared for submission to the National Undergraduate Innovation and Entrepreneurship Training Program. The methodologies and findings have laid the groundwork for a planned JCR Q1 research paper, contributing a novel, data-driven basis for advanced agricultural sorting technologies.