This work presents a novel technique for lifelong localization of robots. It performs a tight fusion of GPS and Multi-State Constraint Kalman Filter, a visual-inertial odometry method for robot localization. It is shown in exper- iments that the proposed algorithm achieves better position accuracy than either GPS and Multi-State Constraint Kalman Filter alone. Additionally, the experiments demonstrate that the algorithm is able to reliably operate when the GPS signal is highly corrupted by noise or even in presence of substantial GPS outages. 1
| Identifer | oai:union.ndltd.org:nusl.cz/oai:invenio.nusl.cz:388082 |
| Date | January 2018 |
| Creators | Krejčí, Tomáš |
| Contributors | Barták, Roman, Obdržálek, David |
| Source Sets | Czech ETDs |
| Language | English |
| Detected Language | English |
| Type | info:eu-repo/semantics/masterThesis |
| Rights | info:eu-repo/semantics/restrictedAccess |
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