The unmanned aerial systems have been developed and emerged with new technologies to achieve the complex missions such as search/rescue, reconnaissance, data acquisition, law enforcement, and mapping terrains etc. In order to enhance the endurance and efficiency of operating these missions, the advancement of guidance, navigation, and control (GNC) algorithms should evolve along the increasing demands of the complex missions in the real world. This research aims to develop the intelligent and collaborative GNC algorithms that are customized specifically for unmanned systems including the fixed-wing vehicles, ground robots, and submarines or any type of robotics. For example, a collision avoidance algorithm is essential for the collaborative systems for completing a mission safely. Additionally, field demonstrations will be performed to verify and validate the developed algorithms with the real systems in an unstructured environment.
LAUNCH students will contribute to make the simulation environment for the fixed-wing vehicle (so called dynamic modeling) and prepare for the flight test (hands-on work). Specifically, they can learn how the autonomous system works, what components are imperative for the autonomy and what hands-on skills are needed for the avionics. They are expected to work with the graduate students or faculty members for building the avionics and learn how to use ROS (Robot Operating System) for the hardware-in-the-loop test bed. Therefore, LAUNCH students can develop the comprehensive research experience in the collaborative autonomous systems.
Project Mentor: Dr. A Ram (Bella) Kim