Date of Award

Summer 2020

Degree Type


Degree Name

Master of Science (MS)


Electrical Engineering

Committee Chair

Bryce Hill

First Advisor

Kevin Negus

Second Advisor

Josh Wold

Third Advisor

Curtis Link


Many challenges arise when attempting to use unmanned aerial vehicles (UAVs) in indoor environments, such as the lack of a GPS signal for use in navigation and the smaller margin of error in movements. Typically, those challenges are addressed by using a collision avoidance system. However, most commercially available collision avoidance systems are expensive, limited in suppliers, and are restricted to use on a specific platform. Additionally, some of the collision avoidance systems choose to forego obstacle detection in one or more directions, usually the upward direction. This work proposes that it is possible to develop a custom, low-cost collision avoidance system with modular capabilities, allowing it to be adapted to any UAV platform. The feasibility of the proposed system was determined by creating a single-direction prototype that was implemented on a small quadcopter and tested by flying the quadcopter towards a wall at slow speeds. To develop the system’s control algorithm a model of a quadcopter was built. Two different control algorithms were developed and tested via simulation with the model, and the better performing algorithm was implemented in the prototype. The feasibility of the proposed collision avoidance system is promising with the prototype able to prevent the quadcopter from colliding with a wall. However, further refinement in the methodology and techniques used to develop the system is needed to improve performance and reliability of the system, especially as obstacle detection is added in other directions of motion. Keywords:


A thesis submitted in partial fulfillment of the requirements for the degree of Masters of Science Electrical Engineering