Session:

MSA - Military and Security Applications of Evolutionary Computation

Title:

Model-Solution Framework for Minimal Risk Planning for URAVs

Authors:

Amit Agarwal
Meng-Hiot Lim
Meng-Joo Er

Abstract:

Waypoint planning for unmanned reconnaissance aerial vehicles (URAVs) used in defense must include the goal of risk-minimization. The external risks may be lowered by minimizing revisitations, coordinating the timing of operation or, flying along vectors that minimize the URAV's signature visible to hostile units. Earlier, we focused on the former and introduced a threat-model, the minimal risk density target visitation (MRDTV) graph, whose vertices are the airbase and the reconnaissance sites and, edges are minimal risk density paths obtained from a bounded Voronoi Graph of in-route threats. Here, we mention several objectives that are consistent with the goal of lowering risks for URAVs from static, in-route, ground-based threats. We discuss how the expressive power of our model can be enhanced and our solution methodology (GAs) be tweaked to provide a broader set of solutions. Our threat-model and solution approach are more suited to low to medium altitude medium endurance URAVs.