Tesis
Um sistema de baixo custo para localização utilizando sensores posicionais e estereoscopia visual
Fecha
2016-08-26Autor
Speroni, Eduardo Arrial
Institución
Resumen
One of the problems in robotics is called Simultaneous Location and Mapping (SLAM), and
lies in the necessity of a robot to localize itself on the environment while simultaneously
mapping it. The use of stereoscopic systems is one approach to solve this problem. Theses
systems are composed by high cost cameras synchronized via hardware, while low cost
cameras are more restrict to applications with low or no movement. This research proposes
a low cost system by using stereoscopy with a low baseline and low horizontal field of view
cameras, synchronizing them via software, along with a filter based on the density of the
disparity map of the captured images, with the intent to discard badly rectified frames, which
implies desynchronization. Additionally, an Android app capable of obtaining and transmitting
sensory data from a smartphone, like GPS and orientation, was developed, reducing
the cost and increasing the system’s accessibility. From these data, calibration and processing
datasets were generated, so they could be analyzed afterward. The combination of
visual odometry and the smartphone’s sensory data contained in the datasets resulted in a
system capable of obtaining its localization without previous knowledge of the environment
with a similar error to the ones obtained by well established high cost techniques. However,
the GPS data was imprecise in low speed scenarios, while the high electromagnetic interference
and the low amount of lateral points of reference harmed the device’s orientation
data and the visual odometry calculation in the high speed scenario. The system isn’t capable
of real time processing, given the need to analyze every frame so they can be filtered,
discarding about 60% of them. It was demonstrated that the proposed low cost system was
capable of keeping a low error in return of a high processing time, potentially reducing the
cost and increasing the accessibility of VSLAM applications. Due to the system’s modularity,
it’s possible to replace its components without many implementation changes, allowing
the use of better precision devices in future work.