"Information Driven UAV Mata Mules in Sparse Sensor Networks"


November 9th (Tuesday), 4:00pm
HFH 4164


In this talk I will discuss the problem data exfiltration from a collection of sensors that are unable to establish ad-hoc communication due to their widespread deployment, geographical constraints, and power considerations. Sensor data is harvested by one or more uninhabited aerial vehicles (UAVs) that visit each sensor in order to establish a communication link. In many applications, the sequence in which the UAVs visit the sensors can have large impact on the overall performance because some sensors have more informative data than others and because distant nodes take a long time to visit. One such application that I will focus on in this talk is the acoustic source localization problem in which the objective is to localize the source of a transient acoustic event as quickly as possible. I will introduce a method based on a minimization of the volume of the Cramer-Rao uncertainty ellipsoid and show significant performance benefits over several other routing protocols using a high-fidelity online simulation environment.

In the second half of the talk I will discuss the problem of finding the minimum length curvature constrained closed path through a set of regions in the plane. This problem is referred to as the Dubins Traveling Salesperson Problem with Neighborhoods (DTSPN), where the Dubins vehicle is a mathematical model for the kinematics of a fixed wing aircraft and the neighborhoods represent a region of the state space of the Dubins vehicle where communication is possible with a sensor on the ground. An algorithm is presented that transforms this infinite dimensional combinatorial optimization problem into a finite dimensional asymmetric TSP by sampling and applying the appropriate transformations, thus allowing the use of existing approximation algorithms. This algorithm is shows significant improvement over existing algorithms for the case where there is a great deal of overlap in the regions.

About Jason T. Isaacs:

Jason T. Isaacs completed his undergraduate education at the University of Kentucky in 1999. Upon graduation he spent the next six years working as a motion control development engineer for Lexmark International Incorporated focusing on the paper feeding systems of inkjet printers. In 2006 he enrolled in the ECE department at UCSB, and earned a MS in 2008.

Hosted by: CCDC/Professor Joao Hespanha