ABSTRACT
Current instances of unmanned aerial vehicles (UAV) tend to fly far away from any obstacles, such as ground, trees, and buildings. This is mainly due to aerial platforms featuring such tremendous constraints in terms of manoeuvrability and weight that enabling them to actively avoid collisions in cluttered or confined environments is highly challenging. Very often, researchers and developers use GPS (Global Positioning System) as the main source of sensing information to achieve what is commonly known as “waypoint navigation”. By carefully choosing the way-points in advance, it is easy to make sure that the resulting path will be free of static obstacles. It is indeed striking to see how research in flying robotics has evolved since the availability of GPS during the mid-1990’s
(1) . GPS enables a flying robot to
be aware of its state with respect to a global inertial coordinate system and – in some respects – to be considered as an end-effector of a robotic arm that has a certain workspace in which it can be precisely positioned. Although localisation and obstacle avoidance are two central themes in terrestrial robotics research, they have been somewhat ignored in the aerial robotics community, since it was possible to effortlessly solve the first one by the use of GPS and ignore the second as the sky is far less obstructed than the Earth surface.
