Introduction to the special issue on aerial robotics

Aerial robotics has been an active area of research for several decades. It has been steadily maturing throughout the years leading to sophisticated auto-pilot systems for manned vehicles and fully autonomous flight and navigation systems for a range of military and civil applications. Nowadays, the emergence of modern embedded computing, sophisticated GPS positioning and the availability of low cost MEMS sensor systems, along with a growing hobby market in low-cost lightweight remote controlled aerial vehicles has opened a vast range of new civil and military applications. The commercial landscape of aerial robotics is characterized by a plethora of small start-up companies marketing specialized platforms for specific applications. The growth in commercial interest has in turn fueled significant growth in research effort in the field of aerial robotics, particularly in the systems and control community. Many of the practical challenges associated with real time implementation of control and estimation algorithms for aerial robotic vehicles are yet to be satisfactorily resolved. Aerial robotic vehicles have complex and poorly known dynamic models. The sensor systems used can be noisy and poorly characterized. The applications considered may require them to be flown closer to the vehicle performance limitations than for manned vehicles. They are often flown in close proximity to an unknown, or only partially known, and dynamically changing physical environment. They might be designed to fly indoors or in an environment where GPS signals are not available. These practical requirements and constraints lead to a field that will benefit tremendously from the application of sophisticated control and estimation techniques. Successful control and estimation algorithms must deal with the inherently nonlinear and poorly known dynamic models of the vehicles. They should deliver global or at least semi-global stability that is robust to dynamically changing environment conditions. They must be designed with the underlying nonEuclidean nature of the state representation of a flying vehicle in mind, typically the special Euclidean group SE(3) for pose control or the special orthogonal group SO(3) for attitude control. They should be tailored to work naturally with the sensor systems that can be effectively mounted on an aerial vehicle and deal with the high noise levels of such sensors. Robust and nonlinear control and estimation algorithms offer the potential to significantly improve the overall performance of aerial robotic systems. The objective of this special issue is to report some recent results in the systems and control field as it applies to aerial robotics, especially those that identify pertinent practical and theoretical open problems, as well as efficient implementations in