The ARS team is part of the Control Optimization and Robotics (COR) laboratory (http://cor.unisalento.it) at the Università del Salento and collaborates with the Institute for Optics (INO) at CNR. COR is an interdisciplinary research group in the area of control engineering and robotics.
The main research activities involve motion coordination of multi-agent systems, distributed control and optimization, aggressive maneuvering of autonomous vehicles, fault diagnosis and reconfiguration, underwater robotics, mobile robotics.
As regards the specific research topics of the project, the participants of the COR group have been involved in the European research projects (FP7) CHAT (Control of Heterogeneous Automation Systems: Technologies for scalability, reconfigurability and security) and CO3AUV (Cooperative Cognitive Control for Autonomous Underwater Vehicles), in the network of excellence HYCON 2 (Highly-‐complex and networked control systems) as level 2 partners, and have been the organizers of the IFAC International Symposium on Intelligent Autonomous Vehicles (IAV) 2010.
The team member of the INO Institute has strong expertise in the field of computer vision and pattern recognition, chemical sensor analysis, non-‐invasive diagnostics of objects in several fields ranging from assistive technology, video analytics for audience measurements and sports events, medical imaging, security and manufacturing.
The team can take advantage from a set of facilities available in the two institutes, including autonomous robots, HD cameras and high performance GPUs. Moreover, an aerial robotics arena is under development in the COR lab. A motion capture system with 10 cameras is already available as well as three quad-‐rotors and two nano quad-‐rotors. Nine more multi‐rotors and five fixed-‐wing UAVs are going to be acquired, in order to have a competitive aerial robotics testbed.
The ARS team is a multi-‐disciplinary group including researcher in the fields of Controls and Robotics, Flight mechanics and dynamics, and Image Processing. Due to its threefold expertise the team is well equipped to tackle the threefold nature of the challenge. That is, the strong flight mechanics and controls expertise of the group, as it appears from publications [1,4,5,7], will give the team excellent skills to perform the modelling, dynamic analysis, and control tasks.
At the same time the strong expertise in state estimation, image processing and pattern recognition, see, e.g., [2,3,6], will allow the team to address the challenging goals of the vision-‐based localization and reconstruction tasks.
 Avanzini, G., Thomson, D., Torasso, A. Model predictive control architecture for rotorcraft inverse simulation, Journal of Guidance, Control, and Dynamics, (2013).
 Distante C and Indiveri G, RANSAC-‐LEL: An optimized version with Least Entropy Like Estimators. Proc IEEE International Conference on Image Processing (2011).
 Leo M, Cazzato D, De Marco T, Distante. An Unsupervised Approach for the Accurate Localization of the Pupils in Near-‐Frontal Facial Images. Journal of Electronic Imaging (2013).
 Rucco A., Notarstefano G., and Hauser J., “Optimal control based dynamics exploration of a rigid car with longitudinal load transfer,” IEEE Transactions on Control Systems Technology (2013)
 Spedicato S., Notarstefano G., Bulthoff H. H., Franchi A. . Aggressive Maneuver Regulation of a Quadrotor UAV. The 16th International Symposium on Robotics Research, Singapore (2013).
 Parlangeli G, Indiveri G., Preliminary results on the active pose estimation of underwater vehicles from range measurements, IFAC Conf. on Control Applications in Marine Systems (2013)
 Piacenza, I.A., Giulietti, F., Avanzini, G. Inverse simulation of unconventional maneuvers for a quadcopter with tilting rotors IFAC Proceedings Volumes (2013).