The work focuses on the robot indoor navigations simulation framework using different artificial intelligence algorithms. This work analyzes different parameters, such as radio beacon enablement and signal/noise level influence of the robot measured position in simulation using Kalman and particle filters algorithms. First section studies currently available artificial algorithms used for indoor navigations, robot used sensors and radio beams and their protocols. Second part focuses on simulation concept of an indoor robot navigation framework, analyzes two simulation models – with and without radio beacon support. Furthermore the study is done regards signal / noise level in sensors influence to the position error. The conclusion concentrates on the results analysis and propositions. During the fork a full-scale simulation framework was created with ability to plug-in different navigation algorithms. Thesis consists of: 59 p. text without appendixes, 29 pictures, 5 tables, 18 bibliographical entries.
Skirtingų tipų dirbtinio intelekto algoritmų panaudojimas uždarųjų patalpų navigacijoje ; Different types of artificial intelligence algorithms use for indoor navigation
2017-06-06
Hochschulschrift
Elektronische Ressource
Lithuanian , Englisch
DDC: | 629 |