A vision-based dual anticipatory/reactive control architecture for indoor navigation of an unmanned aerial vehicle using visual topological maps

Abstract

Indoor navigation of an unmanned aerial vehicle is the topic of this article. A dual feedforward/feedback architecture has been used as the UAV́s controller and the K-NN classifier using the gray level image histogram as discriminant variables has been applied for landmarks recognition. After a brief description of the aerial vehicle we identify the two main components of its autonomous navigation, namely, the landmark recognition and the controller. Afterwards, the paper describes the experimental setup and discusses the experimental results centered mainly on the basic UAV́s behavior of landmark approximation which in topological navigation is known as the beaconing or homing problem. © 2013 Springer-Verlag.