Nathan Hervey

Graduation Semester and Year




Document Type


Degree Name

Master of Science in Computer Science


Computer Science and Engineering

First Advisor

Taylor Johnson


With the increasing availability of mobile robotic platforms, interest in swarm robotics has been growing rapidly. The coordinated effort of many robots has the potential to perform a myriad of useful and possibly dangerous tasks, including search and rescue missions, mapping of hostile environments, and military operations. However, more research is needed before these types of capabilities can be fully realized. In a laboratory setting, a localization system is typically required to track robots, but most available systems are expensive and require tedious calibration. Additionally, dynamical models of the robots are needed to develop suitable control methods, and software must be written to execute the desired tasks. In this thesis, a new video localization system is presented utilizing circle detection to track circular robots. This system is low cost, provides ~ 0.5 centimeter accuracy, and requires minimal calibration. A dynamical model for planar motion of a quadrotor is derived, and a controller is developed using the model. This controller is integrated into StarL, a framework enabling development of distributed robotic applications, to allow a Parrot Cargo Minidrone to visit waypoints in the x-y plane. Finally, two StarL applications are presented; one to demonstrate the capabilities of the localization system, and another that solves a modified distributed travelling salesman problem where sets of waypoints must be visited in order by multiple robots. The methods presented aim to assist those performing research in swarm robotics by providing a low cost easy to use platform for testing distributed applications with multiple robot types.


Video localization, Swarm robotics, Distributed robotics, Circle detection


Computer Sciences | Physical Sciences and Mathematics


Degree granted by The University of Texas at Arlington