Research Project
Autonomous UAV
Research Team
- Dr. Xiaojun (Ashley) Geng, Electrical and Computer Engineering
Collaborators:
Student Team:
- Charbel Abou Afech, BS Computer Engineering
- Javier Narvaez, BS Computer Engineering
- Gael Esparza Lobatos, BS Computer Engineering
- Cynthia Portillo, BS Computer Engineering
- Evelyn Dominguez, BS Computer Engineering
- Katherine Poz Quijivix, BS Computer Engineering
- Abraham Santiago, BS Electrical Engineering
- Luis A. Meza IV, BS Mechanical Engineering
- Jazmin Martinez, BS Electrical Engineering
- Jonathan Penaloza, BS Electrical Engineering
- Amanda Arst, BS Electrical Engineering
Funding
- Funding Organization:
- Funding Program:
SYNOPSIS
- Fully Autonomous UAV system built using MAVSDK-Python for the C-UASC collegiate competition, executing three flight missions autonomously.
- Runs on Raspberry Pi 5 + Pixhawk (PX4) communicating via MAVLink.
- GPS-based route optimization and timed circuit flying for navigation missions
- YOLOv8 computer vision for real-time aerial ground target detection
Research Questions & Research Objectives
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Execute three autonomous missions: waypoint navigation, circuit time trial, and object localization.
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Implement real-time object detection using YOLOv8.
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Design a safety system enforcing competition boundaries (geofence), altitude limits, and mission timeouts.
Research Methods
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Modular mission architecture with shared lifecycle: pre-flight checks, arm, execute, land, and finally log
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TSP route optimization to minimize waypoint navigation distance
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Lawnmower search pattern in offboard mode with NED velocity commands for systematic area coverage
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YOLOv8 nano + OpenCV for lightweight real-time detection with GPS-proximity deduplication to filter repeated detections
Research Deliverables and Products
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System Components: Raspberry Pi 5, Picamera2, Pixhawk 6C (PX4), Telemetry radio, RC, GPS, and YOLOv8 nano model.
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Fully functional autonomous UAV capable of running all three C-UASC mission and verified in SITL simulation.
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Automated flight logging system recording mission results, GPS detections, and performance data as structured JSON after each run.
Commercialization Opportunities
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Application: Configurable autonomous UAV with fail-safe
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Key Values: Eliminates the need for manual piloting, reduces costs and human error, and enforces safe boundaries automatically
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Potential Customers: Emergency responders, utility companies, delivery companies, and environmental researchers
Research Timeline
Start Date:
End Date: TBD
Lead Researchers:
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Dr. Xiaojun (Ashley) Geng, Electrical and Computer Engineering
Collaborators:
Student Team:
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Charbel Abou Afech, BS Computer Engineering
-
Javier Narvaez, BS Computer Engineering
-
Gael Esparza Lobatos, BS Computer Engineering
-
Cynthia Portillo, BS Computer Engineering
-
Evelyn Dominguez, BS Computer Engineering
-
Katherine Poz Quijivix, BS Computer Engineering
-
Abraham Santiago, BS Electrical Engineering
-
Luis A. Meza IV, BS Mechanical Engineering
-
Jazmin Martinez, BS Electrical Engineering
-
Jonathan Penaloza, BS Electrical Engineering
-
Amanda Arst, BS Electrical Engineering
Funding
- Funding Organization:
- Funding Program: