In recent years, unmanned aerial systems (UAS) and other unmanned systems (UxS) have found their way onto the battleground to extend the reach of military forces, providing essential intelligence, surveillance and reconnaissance (ISR) as well as payload delivery and recovery. The increasing capability of such systems, particularly small and light-weight UxS swarms, has offered the Navy, the Marine Corps, and other military branches a significant opportunity to potentially reduce cost, increase system resiliency, and enhance operation effectiveness. However, one fundamental challenge impeding the wide deployment of small-scale UxS and UxS swarms is energy efficiency particularly in the context of complex military missions. Key performance indexes (KPI) of a mission, such as runtime, payload, and survivability, are often severely limited by the energy efficiency of the system. This project aims to tackle this challenge by investigating the fundamental physics governing the UAS energy performance and improving the mission KPIs through energy-oriented planning, control, and swarm collaboration.
The primary goal of this work is energy-efficient tactical optimization of UAS operations. We will develop an integrated planning and management system to optimize UAV energy performance:
- Planning and control: generating optimal UAS trajectory/maneuver sequence to maximize mission efficiency and runtime; and
- Power management: monitoring, diagnosing and managing the critical states of the energy device (battery) during operation.
Principal Investigators: Xinfan Lin and Zhaodan Kong
Additional Staff: Nelson Dichter, Wei Peng, Nicolas Michel, Anish Kumar Sinha
Graduate Students: April Van Hise (military)
Undergraduate Students: Lucas Ang (military)