Multi-sensor data fusion is a broad area of constant research which is applied to a wide variety of fields such as the field of mobile robots. Mobile robots are complex systems where the design and implementation of sensor fusion is a complex task. But research applications are explored constantly. The main objective of a multi-sensor system is to improve the capabilities of a single sensor when translating different sensory inputs into the construction of a map that can be used for navigation. In this context, it is important to find novel solutions based on the state of the art of this field. The scope of the thesis is limited to building a map for a laboratory robot by fusing range readings from a sonar array with landmarks extracted from stereo vision images using the (Scale Invariant Feature Transform) SIFT algorithm.
Sensor Fusion for Autonomous Mobile Robot Navigation
2008-01-01
Plascencia , A 2008 , Sensor Fusion for Autonomous Mobile Robot Navigation . Aalborg Universitet , Aalborg .
Book
Electronic Resource
English
Sensor fusion , Computer vision , Navigation , Mobile robots , Dempster-shafer , Bayes , Sift , Shafer-grids , Mapping
DDC: | 629 |
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