Information Technology Reference
In-Depth Information
A Parallel Multilevel Data Decomposition
Algorithm for Orientation Estimation
of Unmanned Aerial Vehicles
Claudio Paz 1 , Sergio Nesmachnow 2 , and Julio H. Toloza 1
1 Universidad Tecnologica Nacional, Facultad Regional Cordoba, Argentina
{ cpaz,jtoloza } @scdt.frc.utn.edu.ar
2 Universidad de la Republica, Uruguay
sergion@fing.edu.uy
Abstract. Fast orientation estimation of unmanned aerial vehicles is
important for maintain stable flight as well as to perform more complex
task like obstacle avoidance, search, mapping, etc. The orientation esti-
mation can be performed by means of the fusion of different sensors like
accelerometers, gyroscopes and magnetometers, however magnetometers
suffer from high distortion in indoor flights, therefore information from
cameras can be used as a replacement. This article presents a multilevel
decomposition method to process images sent from an unmanned aerial
vehicle to a ground station composed by an heterogeneous set of desktop
computers. The multilevel decomposition is performed using an alter-
native hierarchy called Master/Taskmaster/Slaves in order to minimize
the network latency. Results shows that using this hierarchy the speed
of traditional Master/Slave can be doubled.
Keywords: orientation estimation, unmanned aerial vehicles, high per-
formance computing.
1 Introduction
Nowadays, unmanned aerial vehicles (UAV) generate great interest because they
can replace traditional vehicles which carry out dangerous task like early impact
analysis after a disaster [1], [2], [3], high cost assessment task like atmospheric
surveys [4] or simply for crops analysis [5].
Quadrotors are low cost aerial vehicles, easy to build and maintain because
they consist of a cross shape chassis with four rotors in the corners as shown in
Fig. 1. Due to this shape quadrotors are able to maintain a hovering flight and
perform aggressive maneuvers. Quadrotors flight can be classified in hovering,
navigation and vertical take-of and landing. Fast orientation estimation of a
quadrotor is important for two reason, first, hovering flight demands high speed
controlled thrust on each motor for balance it, and second, in many applications
like autonomous navigation, search, mapping, etc. it is useful to known the full
orientation of the vehicle.
Search WWH ::




Custom Search