Path planning for low-altitude flight by fuzzy reasoning

This paper discusses flight-path planning for an aircraft flying at low altitude while avoiding terrain crashes. In a past study, several algorithms based on exploratory procedures have been proposed; however, they do not generate practical paths that take into account aircraft inertia. This paper proposes a new algorithm to generate a flight path taking account of the aircraft's inertia; this algorithm does not generate the flight path directly, but determines the aircraft's steering acceleration at every point along the way and then generates the flight path based on the steering acceleration. This algorithm extracts feature parameters representing a relation between the aircraft and the terrain, determines steering acceleration by fuzzy reasoning using the feature parameters, and updates state variables of the aircraft. Furthermore, this paper also proposes a learning algorithm to design the membership values in the fuzzy reasoning from reference flights since it is difficult to optimize them by trial and error. The flight-path planning by the proposed algorithm is compared with that based on the exploratory procedure. The learning algorithm of the membership values is validated through computer simulations.