Mentor/s
Okey Ugweje
Participation Type
Poster
Abstract
This project aims to design a system that has the ability to detect objects that could interfere with a drone that is in the process of landing. The implementation of this system includes the use of a 3D Velodyne LiDAR Puck VLP-16, MATLAB, and an Arduino Uno. The system outputs a green light once the program determines it is safe to land and a red light when an object is detected, thus determining it is not safe to land. This project is a continuation and evolution of a past system that used a 2D LiDAR with a tilting mechanism. Current outcomes include running a MATLAB program to receive two values: whether an object is detected, and the distance of that object from the LiDAR. These values are then sent to an Arduino Uno to be displayed to the user through an LCD display. The LiDAR sends UDP packets through the Ethernet port to the computer. These UDP points make up the point clouds (PCs) that the MATLAB code reads. Overall, this abstract seeks to provide a comprehensive understanding of building object detection for a drone with a 3D LiDAR sensor.
College and Major available
Computer Engineering BS, Computer Science BS
Academic Level
Undergraduate student
Location
Digital Commons & West Campus West Building University Commons
Start Day/Time
4-25-2025 12:00 PM
End Day/Time
4-25-2025 2:00 PM
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial 4.0 License
Prize Categories
Most Scholarly Impact or Potential, Most Creative, Best Technology Prototype
Object Detection and Avoidance System using Velodyne 3D LiDAR and MATLAB
Digital Commons & West Campus West Building University Commons
This project aims to design a system that has the ability to detect objects that could interfere with a drone that is in the process of landing. The implementation of this system includes the use of a 3D Velodyne LiDAR Puck VLP-16, MATLAB, and an Arduino Uno. The system outputs a green light once the program determines it is safe to land and a red light when an object is detected, thus determining it is not safe to land. This project is a continuation and evolution of a past system that used a 2D LiDAR with a tilting mechanism. Current outcomes include running a MATLAB program to receive two values: whether an object is detected, and the distance of that object from the LiDAR. These values are then sent to an Arduino Uno to be displayed to the user through an LCD display. The LiDAR sends UDP packets through the Ethernet port to the computer. These UDP points make up the point clouds (PCs) that the MATLAB code reads. Overall, this abstract seeks to provide a comprehensive understanding of building object detection for a drone with a 3D LiDAR sensor.
Students' Information
Terry Ruffin, Computer Engineering Student, graduating May 2025.
Jesse Ortiz, Computer Engineering Student, graduating May 2025.
Julia Piascik, Honors Computer Science and Computer Engineering Student, graduating May 2026.