The goals of this thesis are to modify a full-scale personal hovercraft to perform autonomous maneuvers on flat ground, develop a first principles of the craft, and present data on the vehicle behavior in field trials. The hovercraft, initially designed for manual control by a rider, was modified both physically and with software to allow for remote and autonomous operation. The design leverages the actuator control solutions that are already implemented on the hovercraft for ease of installation and control. A key modification made in the design is the addition of auxiliary fans to increase overall thrust. Controller designs are presented to manage the rotation rate of the added fans. The purpose of the dynamic model is to assist in the design and evaluation of model-based controllers for the vehicle speed and heading. A first principles model was developed to give an approximate understanding of the vehicle's behavior. Data collected during field trials was used to challenge the assumptions made in the first principles model. Based on the field data, the model was updated to provide a better basis to evaluate model based controllers. Additionally, several key observations about the hovercraft performance were noted during the field trials. Controlling the vehicle heading is a nontrivial task and will require a responsive and authoritative controller / Master of Science / Hovercraft are useful vehicles because they can travel over many terrains, including water and land, without being impacted severely by friction. However, they also have several drawbacks including being difficult to steer and having insufficient thrust to scale a steep incline. To address these concerns, we present a design for a modified hovercraft that is capable of being steered with a remote control or with autonomy software. Additionally, eight fans were added to increase the overall thrust of the vehicle to allow it to drive uphill. A model of the hovercraft dynamics was made to allow us to study its behavior. Field trials were conducted to collect data on the hovercraft's performance from the onboard sensors. This data was used to improve the dynamic model so that it can be used in the future to decide the best control design for the hovercraft steering.