Abstract
The work presented in this paper relates to the conceptual definition, simulation, and performance analysis of a novel, 3-D graph theory-based routing algorithm. The proposed router is designed to provide path planning with deconfliction, i.e., collision avoidance with other moving objects, for unmanned aerial vehicles (UAV) applications in general and autonomous UAV missions in particular. Thus, novel ways for "sampling" 3-D operating spaces containing hazard areas and other moving objects are presented. The router operates in a way that conforms to the commonly observed behavior of aircraft flying over relatively long periods of time at constant speed and barometric height. Thus, flying is restricted to a number of possible altitude bands, where changes in altitude and/or direction are restricted to values that ensure excessive airframe stress is avoided. The paper attaches considerable emphasis on algorithmic complexity reduction and develops a novel, adaptive, graph search scheme. The proposed router can also be used to support manned aircraft operation, both for pre-flight planning and during the mission as a pilot aid. Computer simulation results are indicative of a routing system which generates realistic flyable routes while algorithmic complexity is suppressed.