On Thursday 28 November 2013 Lanah Evers will defend her PhD thesis entitled 'Robust and Agile UAV Mission Planning'. Her supervisor is professor Albert Wagelmans (Erasmus School of Economics) and her co-supervisors are dr. Ana Martins Botto de Barros (TNO) and dr. Herman Monsuur (NLDA). Other members of the doctoral committee are professor Rommert Dekker (Erasmus School of Economics), professor Maarten van der Vlerk (Rijksuniversiteit Groningen) and dr. Dennis Huisman (Erasmus University).
Time and location
The PhD defence will take place in the Senate Hall of Erasmus University Rotterdam and will start at 11.30 hrs.
About the dissertation
Unmanned Aerial Vehicles (UAVs) have been a recurring theme in the media in recent years. Although they are now being put to use more and more in commercial settings, these tools are mainly known for their role in conflict situations. In her dissertation entitled Robust and Agile UAV Mission Planning, Lanah Evers deals with problems of uncertainty in flight plans.
On information gathering missions, UAVs may have several different targets that vary in priority and geographical location. Lanah’s research addresses the problem of taking into account various targets with different priorities, combined with fuel and recording constraints that are inherent to the aircraft.
Flight plans also have to deal with a certain level of uncertainty, meaning that the mission may change after starting. Evers develops mathematical models that work out optimal flight plans, allowing for 'in-flight' changes.
With some elaboration and alteration these methods could be put to use for commercial goals. Optimisation of delivery schedules under uncertainty is an example of where this type of research could be used to gain business advantages, allowing companies to factor uncertainty and hence mid-route alterations into their deliveries.
About Lanah Evers
Lanah Evers started her PhD in September 2009. The PhD research was a collaborative research project between TNO, the Netherlands Defence Academy (NLDA) and Erasmus University Rotterdam.
In 2009, Lanah obtained her Master of Science in Econometrics and Management Science (specialisation Operations Research and Quantitative Logistics) at the Erasmus School of Economics, as well as her Master of Science in Teaching Mathematics at the University of Leiden, both with honours. Lanah combined her studies with sports, and with different jobs. The sports include judo, boxing and fitness. The jobs include part-time work as a business analyst at the Actuarial and Employee Benefits division of Deloitte in Rotterdam, ambassadorship and teaching assistance at the Erasmus School of Economics, and teaching Mathematics to high school students at the Luzac College in Bergen op Zoom for almost three years.
Lanah currently works at Quintiq, a specialised supply chain planning and optimisation software company.
Abstract of 'Robust and Agile UAV Mission Planning'
This PhD thesis presents new robust and agile planning methods to improve the effectiveness and efficiency of Unmanned Aerial Vehicle (UAV) mission planning. UAV's are often used in reconnaissance missions to capture both motion and still imagery of potential 'targets' on which up-to-date information is required. Such targets might include important infrastructure, possible locations of Improvised Explosive Devices (IEDs), and insurgent locations.
The goal of the UAV mission is thus to gather as much information as possible given operational constraints related to the UAV endurance capabilities. Obviously, some locations might be more relevant than others in terms of information gathering supporting the military objective. In order to optimize data collection, the UAV mission should include targets of higher relevance, starting and ending at the UAV recovery point. Existing mathematical models could be used to optimise this UAV mission planning problem.
However, the existing models do not take the uncertainty and dynamics of the problem into account in the planning stage, and might therefore result in infeasible or suboptimal flight plans.
This thesis introduces new mathematical models for the UAV mission planning problem which explicitly consider uncertainty in fuel consumption, flight and recording times, time windows and a dynamically changing set of targets.