Planetary rovers are robots that need to perform autonomous navigation, because of the long delay communication and no human assistance. Furthermore, they need to perform the optimal estimation of its position in order to have a good performance on its navigation system. The need for good performance filters for estimating the actual position of mobile robots of this kind is needed, due to the fact that sensors are noisy and that information is of vital importance for a planetary rover’s mission. Besides, good accurate sensors for the matter, are not easy to find for space application. Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF) were implemented to analyze a data set of a 4-wheel robot, and later used for comparison on accuracy in the estimation of its pose. The analysis will give the possibility to know the right combination of sensors, recognize some issues during the trajectory. Furthermore, this study has been made with aims to give the reader knowledge of state of the art in planetary rovers, their constraints and consideration while developing them. The robot used for the research has been developed for an international competition of field robot automation. The main goal is to navigate autonomously through flowerpots performing different tasks as flowerpot collection, distance traveled and robustness on localization and navigation algorithms. / <p>Validerat; 20120822 (anonymous)</p>
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:ltu-44577 |
| Date | January 2012 |
| Creators | Sosa Cruz, Roberto |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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