The focus of the present thesis is on the joint use of cameras and inertial sensors, a
recent area of active research. Within our scope, the performance of body state
estimation is investigated with isolated inertial sensors, isolated cameras and finally
with a fusion of two types of sensors within a Kalman Filtering framework. The
study consists of both simulation and real hardware experiments. The body state
estimation problem is restricted to a single axis rotation where we estimate turn angle
and turn rate. This experimental setup provides a simple but effective means of
assessing the benefits of the fusion process. Additionally, a sensitivity analysis is
carried out in our simulation experiments to explore the sensitivity of the estimation
performance to varying levels of calibration errors. It is shown by experiments that
state estimation is more robust to calibration errors when the sensors are used jointly.
For the fusion of sensors, the Indirect Kalman Filter is considered as well as the
Direct Form Kalman Filter. This comparative study allows us to assess the
contribution of an accurate system dynamical model to the final state estimates.
Our simulation and real hardware experiments effectively show that the fusion of the
sensors eliminate the unbounded error growth characteristic of inertial sensors while
final state estimation outperforms the use of cameras alone. Overall we can
v
demonstrate that the Kalman based fusion result in bounded error, high performance
estimation of body state. The results are promising and suggest that these benefits
can be extended to body state estimation for multiple degrees of freedom.
| Identifer | oai:union.ndltd.org:METU/oai:etd.lib.metu.edu.tr:http://etd.lib.metu.edu.tr/upload/12611122/index.pdf |
| Date | 01 September 2009 |
| Creators | Aslan Aydemir, Gokcen |
| Contributors | Saranli, Afsar |
| Publisher | METU |
| Source Sets | Middle East Technical Univ. |
| Language | English |
| Detected Language | English |
| Type | M.S. Thesis |
| Format | text/pdf |
| Rights | To liberate the content for public access |
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