Abstract: The recent technological advances in the field of autonomous vehicles have resulted in a growing impetus for researchers to improve the current framework of mission planning and execution within both the military and civilian contexts. The interest in applications involving autonomous vehicles is expected to grow significantly in the near future as new paradigms for their use are constantly being proposed for a diverse spectrum of real world applications. In this talk I will present a framework for addressing vehicle-target assignment problems involving either a team of autonomous vehicles with a single target (multi-vehicle scenario) or a single vehicle with multiple targets (multi-target scenario) that is aimed at reducing the complexity of the assignment problem. In particular, I will introduce a Voronoi-type partition of the space populated by the vehicles and the targets, which divides the space into a finite number of non-overlapping sets. These sets correspond to the “areas of influence” of each vehicle or target. The key feature of the proposed partitioning scheme is that the proximity relations between the vehicles and the targets are induced by state-dependent (pseudo-) metrics, such as the minimum time-to-go, rather than the Euclidean distance or other generalized distance functions used in the literature. These state-dependent metrics can, in contrast to more “conventional” distance functions, succinctly capture essential features of the vehicle’s maneuverability as well as the environment-vehicle interactions, which are induced, for example, by local winds/currents. Subsequently, I will illustrate how the proposed concept of state-dependent spatial partition can be applied to a group pursuit problem of a maneuvering target. I will also discuss a multi-target version of the Zermelo navigation problem for a small UAV in the presence of a strong wind field and/or when the ensuing path of the UAV satisfies the explicit curvature constraints of the Markov-Dubins problem.

Bio: Efstathios Bakolas is a Post-doctoral Fellow in the School of Aerospace Engineering at the Georgia Institute of Technology. He received his Diploma in Mechanical Engineering from the National Technical University of Athens, Greece, in 2004 and his MS. and PhD. degrees in Aerospace Engineering from Georgia Institute of Technology in 2007 and 2011, respectively. His current research interests are in the area of guidance, navigation, and control with an emphasis on applications of autonomous vehicles using optimal control and differential game theory.