무인 이동체의 계산 효율을 고려한 가우시안 프로세스 회귀 기반 외란 대처 경로 추종 유도 기법 설계

Abstract

In this study, we propose a Gaussian Process Regression-based disturbance rejection path-following guidance law to enable unmanned vehicles to precisely follow predefined paths in the presence of disturbances such as wind. The baseline guidance algorithm is designed by feedback linearization and optimal error dynamics. The Gaussian process regression through the Kalman filter is introduced to reduce the complexity of the classic Gaussian process regression for estimating the disturbances. Through simulations, the performance of the designed disturbance rejection path-following algorithm is validated.