Jay Robert B. del Rosario

About

Jay Robert B. del Rosario is a robotics researcher whose work focuses on autonomous navigation, embedded systems, and mobile robotics. His most cited paper, "Modelling and Characterization of a Maze-Solving Mobile Robot Using Wall Follower Algorithm" (2013, 11 citations), introduces a PIC microcontroller-based robot capable of autonomously navigating and solving mazes, drawing inspiration from micromouse competitions. This foundational work demonstrates his expertise in algorithm implementation and real-world robotic problem-solving. Del Rosario further advanced autonomous systems with his research on quadrotors, specifically in "Development of a Quadrotor with Vision-based Target Detection for Autonomous Landing" (2018, 6 citations), which explores computer vision techniques for precise drone landing—a critical challenge in unmanned aerial vehicle applications. His additional work on maze-solving robots that track traversed distance (2018, 2 citations) underscores his commitment to improving robot localization and mapping capabilities. Collectively, del Rosario’s contributions bridge theoretical algorithms with practical robotics, offering valuable insights for students and researchers in autonomous navigation, embedded control, and vision-guided systems.

Research Focus

Key Achievements

Top Papers

1. 1
   Modelling and Characterization of a Maze-Solving Mobile Robot Using Wall Follower Algorithm

   11 citations · 2013
2. 2
   Development of a Quadrotor with Vision-based Target Detection for Autonomous Landing

   6 citations · 2018
3. 3
   Development of a Maze Solving Mobile Robot Capable of Tracking the Distance It Traversed

   2 citations · 2018

Key Collaborators

Contact & Links