Rotorcraft shipboard landing guidance using MPPI trajectory optimization

Abstract

With shipboard launch and recovery operations remaining a challenge, there is a continuing emphasis to determine pilot assist functions in order to reduce pilot workload arising from handling the effects of ship air wake turbulence, random ship motion and degraded visuals associated with this task. This paper is an extension to previous work which investigated the use of Model Predictive Path Integral (MPPI) approach, a stochastic optimal control method, for trajectory guidance during shipboard landing. With the objective of developing a real-time guidance solution, this paper focuses on understanding the effect of the performance measure and parameters associated with the method by using a linear model for prediction and a nonlinear model as a representation of the actual vehicle. First, in continuation with an earlier paper, a simple study is conducted by including yaw attitude constraint during shipboard landing using a six degrees-of-freedom linear model of the helicopter in the MPPI method. Next, a test is conducted where a linear model is used in the MPPI algorithm to predict the helicopter behavior for the entire landing with a nonlinear model serving as the truth model. Lastly, the effect of prediction window on MPPI performance is investigated. The paper concludes with key observations and inferences gained in this study.