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| Author(s): |
Vitor Campanholo Guizilini
Total Authors: 1
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| Document type: | Master's Dissertation |
| Press: | São Paulo. |
| Institution: | Universidade de São Paulo (USP). Escola Politécnica (EP/BC) |
| Defense date: | 2008-08-12 |
| Examining board members: |
Jun Okamoto Junior;
Anna Helena Reali Costa;
Denis Fernando Wolf
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| Advisor: | Jun Okamoto Junior |
| Abstract | |
The problem of simultaneous localization and mapping, known as the problem of SLAM, is one of the greatest obstacles that the field of autonomous robotics faces nowadays. This problem is related to a robots ability to navigate through an unknown environment, constructing a map of the regions it has already visited at the same time as localizing itself on this map. The imprecision inherent to the sensors used to collect information generates errors that accumulate over time, not allowing for a precise estimation of localization and mapping when used directly. SLAM algorithms try to eliminate these errors by taking advantage of their mutual dependence and solving both problems simultaneously, using the results of one step to refine the estimatives of the other. One possible way to achieve this is the establishment of landmarks in the environment that the robot can use as points of reference to localize itself while it navigates. This work presents a solution to the problem of SLAM using an omnidirectional vision system to detect these landmarks. The choice of visual sensors allows for the extraction of natural landmarks and robust matching under different points of view, as the robot moves through the environment. The omnidirectional vision amplifies the field of vision of the robot, increasing the number of landmarks observed at each instant. The detected landmarks are added to the map, and when they are later recognized they generate information that the robot can use to refine its estimatives of localization and mapping, eliminating accumulated errors and keeping them precise even after long periods of navigation. This solution has been tested in real navigational situations and the results show a substantial improvement in the results compared to those obtained through the direct use of the information collected. (AU) | |
| FAPESP's process: | 06/05293-2 - Simultaneous localization and mapping with omnidirectional vision |
| Grantee: | Vitor Campanholo Guizilini |
| Support Opportunities: | Scholarships in Brazil - Master |