Wednesday, July 2nd
Talk 7: Simon Lacroix, LAAS/CNRS, France
Fixed-wing micro drones have already shown to be valuable tools to sample the atmosphere, e.g. to measure temperature, humidity, pressure, winds, etc. But the fine understanding of meteorological phenomena such as the ones that occur within clouds require samples that span both spatial and time scales. A fleet of drones is well suited for this purpose, as drones can coordinate to adaptively sample the space over periods of the order of one hour. The starting project « SkyScanner » is devoted to the study and experimentation of such a fleet. The talk will sketch the various challenges tackled in the project, from the optimisation of the drones aerodynamics to dynamically evolve within clouds, to the overall adaptive fleet control, via the development of specific instrumentations, and of flight control schemes to harvest as much energy as possible from the measured winds.
Simon Lacroix is a research scientist at LAAS/CNRS, where he animates the field robotics activities. He was mainly involved in planetary robotics during the 90’s, and has initiated aerial robotics activities in the lab in the beginning of the 2000’s. Since then, his research is focused on the deployment of teams of multiple heterogeneous autonomous robots for exploration, surveillance or intervention missions. His main interests originally concerned perception and navigation for autonomous aerial and terrestrial robots (environment perception and modeling, localisation, perception control and autonomous navigation strategies), and have evolved towards decisional processes required by the cooperation within multi-robot teams.
Talk 8: Enric Xargay, University of Illinois at Urbana-Champaign
This talk will outline novel strategies for motion planning and control in support of time-critical cooperative missions, in which a team of autonomous unmanned vehicles must work in cooperation to achieve a common objective subject to spatial and temporal constraints. We will present a new framework for the efficient computation of sets of cooperative, collision-free trajectories, and will also introduce distributed control algorithms that provide guaranteed levels of performance in the presence of faulty communication networks. Special emphasis will be given to algorithms that yield improved vehicle synchronization in communication-limited environments. The talk will also discuss how the proposed solutions can support the integration of unmanned aerial vehicles into non-positively controlled airspace, a critical issue in the realization of the NextGen Air Transportation System. Simulations and flight-test results will demonstrate the efficacy of the multi-vehicle cooperative framework presented.
Enric Xargay (firstname.lastname@example.org) received a Ph.D. in Aerospace Engineering from the University of Illinois at Urbana-Champaign (UIUC) in 2013. Before that, he earned an M.S. in Control Engineering from BarcelonaTech/UPC and an M.S. in Aerospace Engineering from the Politecnico di Torino, both in 2007. Since 2013, he has been with the Department of Mechanical Science and Engineering at UIUC, where he is a postdoctoral research associate. In 2011, he received the Roger A. Strehlow Memorial Award from the Department of Aerospace Engineering at UIUC for outstanding research accomplishment. His research interests include aircraft flight control, nonlinear systems, adaptive control, robust control, and cooperative motion planning and control of autonomous systems.
Talk 9: Christian Claudel, King Abdullah University of Science and Technology, Saudi Arabia
Fixed wing Unmanned Aerial Vehicles (UAVs) are an increasingly common sensing platform, owing to their key advantages: speed, endurance and ability to explore remote areas. While these platforms are highly efficient, they cannot easily be equipped with air data sensors commonly found on their manned counterparts, since these sensors are bulky, expensive and affect the payload capability of the UAV. In consequence, UAV controllers have little information on the actual mode of operation of the wing (normal, stalled, spin) which can cause catastrophic loss of control when flying in turbulent weather conditions. In this talk, we propose a real-time air parameter estimation scheme that can run on commercial, low power autopilots in real-time. The computational method is based on an hybrid decomposition of the modes of operation of the UAV. An implementation on a real UAV is presented, and the accuracy of this method is validated using a hardware in the loop (HIL) simulation.
Christian Claudel is an assistant professor of Electrical Engineering and Mechanical engineering at KAUST. He received the PhD degree in EECS from UC Berkeley in 2010, and the Ms degree in Plasma Physics from Ecole Normale Superieure de Lyon in 2004. He received the Leon Chua Award from UC Berkeley in 2010 for his work on Mobile Millennium. His research interests include control and estimation of distributed parameter systems, wireless sensor networks and environmental sensing systems.