JRV

Portfolio / CASE STUDY

VCU team capstone · 2017

Remote Aerial Mapping Spectrometer.

A self-powered UAV sensor payload combining spectroscopy, laser ranging, and orientation data for environmental mapping.

MY ROLE

Team contributor: programming and 3D modeling; publication coauthor

Why it exists

Environmental researchers need useful spectral information at a local scale. Handheld surveys are slow, while aircraft and satellite hyperspectral systems can be costly or unsuitable for a small study.

What I built

Our VCU team designed a self-powered payload for an unmanned aerial vehicle. A laser rangefinder, spectrometer, and orientation tracking support a three-dimensional map of material signatures. The project explored applications in algal bloom monitoring, forestry, and agriculture.

Engineering decisions

01

Integrate sensing disciplines

RAMS combines geometry and spectral observations. The public C implementation uses concurrent sensor acquisition workers and queues, with MySQL handling captured data. My contribution included programming and 3D modeling.

02

Design around the carrier

A self-powered payload includes the required sensors and aims to work with aircraft that can carry its weight.

03

Engineering as a team

The VCU publication names Kenny Parker, José Ramirez, Chris Lillard, and Quan Ma. The project repository identifies NASA Langley Research Center as sponsor of this university team capstone.

Capabilities in practice

  • Embedded and physical systems
  • Sensor integration
  • Engineering research
  • Cross-disciplinary teamwork

KEEP EXPLORING

STM32 Robotics