<title>Technologies for the unified collection and control of UCAVs</title>

Abstract

The problem of managing swarms of UAVs consists of multi-agent collection (i.e., distributed robust data fusion and interpretation) and multi-agent coordination (i.e., distributed robust platform and sensor monitoring and control). This paper deals with a specific aspect of the latter, namely collision avoidance and trajectory generation problems in the presence of pop-up threats. These problems are difficult to solve because the set of feasible solutions is non-convex, possibly infinite dimensional and defined in terms of an infinite number of constraints. Recent approximation methods use a finite dimensional parameterization of solutions and impose constraints on a finite grid in time. They result in large feasibility problems and are at best only sufficient. We show that there is no need to grid if the admissible trajectories are restricted to polynomials of degree no larger than a specified bound. A finite dimensional necessary and sufficient condition, whose size depends only the assumed degree bound, is derived in this paper. It is used to improve some existing trajectory generation methods, develop new approximation methods and solve a collision avoidance problem exactly. Our techniques clearly show how certain non-convex constraints arising in path planning can be converted to mixed integer/LMI constraints.