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The purpose of our project is to design and implement an obstacle detection and avoidance system for use on multirotor drones. The system gathers information from two Arducam 5MP cameras, using stereoscopic vision as the primary obstacle detection source. It also uses an XL-MaxSonar-EZ3 ultrasonic sensor as a backup, in case the cameras fail to detect an obstacle. All three of these sensors will be mounted to the drone using a 3D printed mounting bracket, to ensure consistency of sensor information. The system will interface with the Naza-M v2 flight controller, overriding the user controls when the user attempts to steer the drone forward into an obstacle. At the same time, the system will light an LED to inform the user of the control override.

The Zybo Zynq-7000 development board is the main processing system used in our project. We utilize the System-on-a-Chip (SoC) development scheme offered by this board, simultaneously developing software for the ARM-9 processor and hardware to implement on the FPGA fabric.

Publication Date



Computer Vision, Semi-autonomous Flight, Real-Time, Embedded Systems


Electrical and Computer Engineering | Engineering

Faculty Advisor/Mentor

Wei Zhang

Faculty Advisor/Mentor

Tim Bakker

VCU Capstone Design Expo Posters


© The Author(s)

Date of Submission

May 2018

Collision Avoidance for Quadcopters