Real-time guidance algorithms for helicopter shipboard landing

Helicopter shipboard landing is one of the most challenging operations for pilots to execute owing to the random ship deck motion, turbulence due to airwake interactions, and poor visibility due to sea sprays, weather conditions and at night. Active research in this field has been focused on developing schemes to either autonomously pilot the vehicle to land on the ship deck or elements to assist the pilot such as guidance and visual cueing schemes, ship deck motion prediction, etc. The first portion of our research focused on developing a real-time guidance algorithm, utilizing Model Predictive Path Integral (MPPI) approach, to predict the helicopter’s future vehicle position and orientation, which is fed to the pilot as a visual cue.

Since pilot workload issues are a limiting factor to define allowable operating conditions for a given helicopter-ship combination, it is crucial to determine the impact of any new pilot-assist guidance-cueing scheme on pilot workload. The second portion of our research is focusing on understanding the term pilot workload, and to determine if an objective metric could be developed by analyzing pilot control activity in the presence and absence of a guidance-cueing scheme. This research direction attempts to answer whether mental workload is captured in pilot control activity and to determine if the introduction of a new guidance-cueing scheme alleviates or transfers pilot workload

Author: Karen Feigh and vcomandur3

Professor of Cognitive Engineering, School of Aerospace Engineering Associate Chair for Research Daniel Guggenheim School of Aerospace Engineering Georgia Institute of Technology

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