Towards a vision-based targeting system for counter unmanned aerial systems (CUAS)

Unmanned aerial vehicles (UAVs) are rapidly increasing in popularity. Despite attempts at regulation, stopping small, Class 1 (typically hobby-grade) UAVs from entering protected or sensitive airspace is an unsolved problem. Many companies and researchers offer a piece of a solution, but as of this writing, there is no publicly available, feasible, end-to-end solution. Ultimately, what is needed is a sensor-based system that autonomously detects, tracks, and neutralizes/disables an incoming UAV. However, such a system is currently not available, so as development toward that goal continues, a temporary solution is required. Augmenting the skill, dexterity, and processing power of human pilots with inexpensive cameras and computer vision algorithms can offer such a solution. The foundations of a framework for a system that uses computer vision to target and ultimately destroy a target in mid-air is introduced. The proposed solution utilizes a light-weight, inexpensive UAV with an on-board camera. The detection and tracking is performed in real-time on a companion computer mounted to the frame of the vehicle, with ROS as the primary communication infrastructure. Initial simulations provide insight into the feasibility of using computer vision with a monocular camera to offer reliable assistance to the pilot.

I. Introduction

Unmanned Aerial Vehicles (UAVs), colloquially known as drones, have continued to increase in popularity. The Department of Defense (DoD) of the United States categorizes UAVs into classes based on their size and capabilities. Class 1 UAVs are defined as small, portable, and self-contained [1]. The UAVs in this category are analogous to model aircrafts. Class 1 UAVs are becoming cheaper and easier to access. Many popular brands of UAVs can be purchased at any large retail chain or hobby store. Improvements in autopilot software allow people to easily fly UAVs autonomously with very little experience required. Several high profile incidents involving Class 1 UAVs [2]–[4] have brought awareness to a gap in security, specifically to the failure of current security measures and protocols to detect and remove potential threats involving Class 1 UAVs [5]. Although there have not been any major damages or casualties caused by Class 1 UAVs at the time of submission, the gap in security does leave the potential for nefarious persons to use them as a means to do harm.