Thesis Details
Určování polohy robota na základě měření ze senzorů
The goal of this thesis is to create a program, that will be receiving measurements from robot's sensors and fuse them together. Afterwards use this data fusion of chosen sensors to estimate location of a robot. As a solution for these problems I have used my knowledge of Kalman filters, especially extended one. If messages from sensor measurements are well formulated, Kalman filter can perform fusion of measurements together with estimating the actual position of a robot. Filter can receive measurements from multiple sources and even from duplicities. The estimated states have proven themselves reasonably accurate for successful robot localization in space.
Data fusion, Global Positioning System, Kalman filter , Extended Kalman filter, Robot localization, Navigation stack, Odometry, Probabilistic robotics, ROS
Burget Lukáš, doc. Ing., Ph.D. (DCGM FIT BUT), člen
Hliněná Dana, doc. RNDr., Ph.D. (DMAT FEEC BUT), člen
Matoušek Petr, doc. Ing., Ph.D., M.A. (DIFS FIT BUT), člen
Zachariášová Marcela, Ing., Ph.D. (DCSY FIT BUT), člen
@bachelorsthesis{FITBT19182, author = "Ondrej \v{C}aklo\v{s}", type = "Bachelor's thesis", title = "Ur\v{c}ov\'{a}n\'{i} polohy robota na z\'{a}klad\v{e} m\v{e}\v{r}en\'{i} ze senzor\r{u}", school = "Brno University of Technology, Faculty of Information Technology", year = 2017, location = "Brno, CZ", language = "czech", url = "https://www.fit.vut.cz/study/thesis/19182/" }