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Aerial robots can be considered as the natural evolution of the Unmanned Aerial Vehicles (UAVs) from the point of view of the intelligence. Traditional industrial robots evolved from the repetition of sequences of previously defined way points, with minimal perception and decision capabilities, toward robots interacting with the environment, mapping unknown environments and localising the robot in these maps. Thus, Simultaneous Localisation and Mapping (SLAM), has played an important role in the exploration of unknown environments. In the same way, Unmanned Aerial Vehicles will also evolve from the current commercial UAVs that mainly move by following a list of way points, to aerial robots capable of perceiving the environment adapting their behaviour to dynamic events. In addition, current UAV navigation strongly depends on satellite positioning systems, and then is sensitive to GPS transient failures, which are common in many outdoor environments. Furthermore, the navigation in GPS denied environments requires positioning devices that could be very costly and/or difficult to be implemented. Therefore, positioning with respect to the perceived environment is a need to increase the reliability or even to make possible UAV navigation. Moreover, environment mapping is also a very desirable feature for many UAV applications. Consequently, simultaneous

Special Issue on: Airborne Simultaneous Localisation and Map Building (A-SLAM)