Papers & Publications
Predictive pickup with a monocular wrist camera: Strategies and parameters for dynamic conveyor grasping Robotics and Computer-Integrated Manufacturing, 2026, First Author
This peer-reviewed article presents and evaluates predictive pickup strategies for grasping moving parts on a conveyor using a wrist-mounted monocular camera. The work compares multiple closed-form approaches for estimating part motion and timing interception, then uses a structured parameter study to quantify how key choices impact alignment error and overall robustness. A major emphasis is practicality: achieving reliable performance with a hardware/software stack that can be deployed without heavy external compute or complex sensing, providing actionable guidance for designing cost-effective automation cells in small-to-medium manufacturing environments.
M.S. Thesis: Implementation, Development, and Evaluation of a Single-Camera Robotic Pick-and-Place System for Dynamic Object Detection, Tracking, and Pickup
Fairfield University, 2025
This master’s thesis documents the end-to-end development and evaluation of a single-camera, vision-guided robotic pick-and-place system designed for dynamic conveyor scenarios. It covers the mechanical and software integration of a wrist-mounted camera, part detection/tracking methods, and the control strategies used to synchronize robot motion with moving targets. The thesis emphasizes experimental rigor: designing repeatable test procedures, isolating variables (e.g., lighting, conveyor speed, camera settings, scan height, iteration count), and analyzing how these factors influence detection reliability and pickup alignment. Beyond performance results, it discusses practical deployment considerations, such as cost, complexity, and constraints typical of small-to-medium manufacturing lines, along with recommendations for improving robustness and future extensions.