Exact knowledge of the position of a vehicle is a fundamental problem in mobile robot applications. A variety of systems and applications have been already been developed for mobile positioning on Earth, but not many of them are suitable for positioning on the Moon. Those methods are based on estimating the position of a robot by integrating an absolute and relative measurementsabsolute and relative measurements. Just like at indoor positioning also at With positioning on the Moon, just like with indoor positioning, there is no Global Navigation Satellite System (GNSS) available. In this case the idea of fusing several systems together becomes viableactive. On one side hand there are relative position measurement systemss such as odometry and inertial navigation and on the other handside there are absolute position measurements such as map matching, landmark based localization and active beacons. For integrating those sensors, a Kalman filter (EKF) is usually is used. The method presented here could be used for positioning a robot indoors or on the Moon. It integrates data gathered from a laser tracker and camera, and then calculates the position of the robot based on the Collins resection method. Data gathered from the experiment and possible locations of the robot are presented at the end. In mathematical calculation, the photogrammetry method and projective geometry were used, to avoid trigonometric and inverse trigonometric functions. In conclusion, all radial and tangential distortions were removed from the images and with the help of the iterative method the smallest deviations were calculated. ; Če nam lokalizacija in pozicioniranje robota na Zemlji danes ne predstavljata več velikega problema, pa nam pozicioniranje na Luni predstavlja še kako velik izziv. Poznavanje točne lokacije mobilnega robota je ključnega pomena za njegovo delovanje. Veliko raziskav in projektov je že bilo izvedenih na to temo, vendar specifične rešitve še ni. Do sedaj so raziskave temeljile na opazovanju Sonca in Zemlje, vendar za kakšno resno raziskovanje Lune takšno pozicioniranje ni dovolj natančno. Pozicioniranje na Luni se lahko primerja z notranjim pozicioniranje na Zemlji. Gre predvsem za to, da tako kot na Luni tudi v notranjosti objektov globalni navigacijski satelitski sistemi za določevanje položaja niso dostopni oziroma ne obstajajo. V tem primeru pride v ospredje ideja združevanja informacij z več različnih senzorjev. Najbolj pogosti senzorji so senzorji pomika (relativna informacija), laserski merilniki razdalj, kamere in radarji (absolutna informacija). Integracija senzorjev za namen lokalizacije je lahko izvedena z Kalmanovim filtrom (EKF), kjer so rezultati pridobljeni s simulacijo kinematičnega modela robota.
Self-positioning of a moving robot ; Pozicioniranje robota
2018-09-12
Theses
Electronic Resource
English
DDC: | 629 |
Control System of a Semi-Autonomous Mobile Robot ; Řídící systém semi-autonomního robota
BASE | 2016
|Vyuziti robota APR 40 pro odporove svarovani dveri autobusu 730
Tema Archive | 1986
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