Mentor/s
Tolga Kaya
Participation Type
Poster
Abstract
This project aims to design a sensing system that will have 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 RPLiDar A2 M8, Jetson Nano, and an Arduino. The system outputs a green light once the program determines it is safe to land and a red light when an object is detected. Notifying the drone of any obstacles is necessary for various reasons, such as military usage. Since this project was built with a two-dimensional sensor, there were issues when adding the third dimension for accurate object detection and avoidance. This issue was solved by adding a tilting mechanism that was 3D-printed with two motors to hold and move the sensor in a range from zero to sixty degrees. Current outcomes include successfully booting and scanning an area with the LiDar and plotting polar coordinates through a Python program. It is expected that with the 3D-printed tilting mechanism, the Python program will combine the X and Y planes from the 360-degree scan with the Z planes from the tilting to plot clusters in a polar graph to show when an object is detected. Depending on whether clusters are detected in the specified range of five feet, the red light or green light will flash.
College and Major available
Computer Engineering BS, Computer Science BS, Electrical Engineering BS
Location
Digital Commons & West Campus West Building University Commons
Start Day/Time
4-26-2024 12:00 PM
End Day/Time
4-26-2024 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 using RPLiDar A2M8 and Jetson Nano
Digital Commons & West Campus West Building University Commons
This project aims to design a sensing system that will have 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 RPLiDar A2 M8, Jetson Nano, and an Arduino. The system outputs a green light once the program determines it is safe to land and a red light when an object is detected. Notifying the drone of any obstacles is necessary for various reasons, such as military usage. Since this project was built with a two-dimensional sensor, there were issues when adding the third dimension for accurate object detection and avoidance. This issue was solved by adding a tilting mechanism that was 3D-printed with two motors to hold and move the sensor in a range from zero to sixty degrees. Current outcomes include successfully booting and scanning an area with the LiDar and plotting polar coordinates through a Python program. It is expected that with the 3D-printed tilting mechanism, the Python program will combine the X and Y planes from the 360-degree scan with the Z planes from the tilting to plot clusters in a polar graph to show when an object is detected. Depending on whether clusters are detected in the specified range of five feet, the red light or green light will flash.
Students' Information
Mateo Cappuccio, Electrical Engineering, graduating in December 2024.
Logan Ward, Electrical Engineering, graduating May 2024.
Julia Piascik, Honors Computer Science and Computer Engineering Student, graduating in May 2026.
Honorable Mention, Most Scholarly Impact or Potential 2024 Award