The objective of this SBIR Phase I is the development of a system-level hardware-software architecture and algorithms for a backup shipboard landing system for VTOL UAVs. The proposed system is comprised of a combination of a multi-modal sensor suite and a synergistic combination of algorithmic components including data fusion, perception, stochastic motion prediction, path planning, decision making, and inner-loop controls. The proposed effort demonstrates the feasibility of our approach through system-level design, identification of the sensor suite, development of the required algorithms, implementation of a demonstration software prototype of the algorithms, and simulation studies to demonstrate viability of the proposed system. The Phase I effort will provide a solid foundation for carrying out the Phase II objectives which would encompass implementation and integration of the entire suite of constituent algorithms within the system, integration of a hardware-software prototype of the system, Hardware-In-The-Loop simulation studies, and performance demonstration through experimental flight trials. While the primary focus in the design of the shipboard landing system in this proposal is on mid-size VTOL UAVs such as the Northrop Grumman Fire Scout, the system to be developed and the underlying technologies can address a wide range of VTOL UAV and ship platforms.
Benefit: There are several military and civilian applications of an autonomous landing system for VTOL UAVs including search and rescue, reconnaissance, surveillance, recovery, battle damage assessment, port security, border patrol, fire fighting, pipeline monitoring and inspection, weather monitoring, remote sensing, disaster relief.
Keywords: data fusion, data fusion, Autonomous landing system, VTOL, UAV, Shipboard Landing, Motion Prediction, perception, precision relative navigation