There has always been a desire to apply technology to human endeavors to increase
a person's capabilities and reduce the numbers or skill level required of the
people involved, or replace the people altogether. Three fundamental areas are investigated
where technology can enable the reduction or removal of humans in complex
tasks.
The fi rst area of research is the rapid calibration of multiple camera systems
when cameras share an overlapping fi eld of view allowing for 3D computer vision
applications. A simple method for the rapid calibration of such systems is introduced.
The second area of research is the autonomous exploration of hallways or other urbancanyon
environments in the absence of a global positions system (GPS) using only
an inertial motion unit (IMU) and a monocular camera. Desired paths that generate
accurate vehicle state estimates for simple ground vehicles are identi fied and the
bene fits of integrated estimation and control are investigated. It is demonstrated
that considering estimation accuracy is essential to produce efficient guidance and
control. The Schmidt-Kalman filter is applied to the vision-aided inertial navigation system in a novel manner, reducing the state vector size signi ficantly. The final area
of research is a decentralized swarm based approach to source localization using a
high fidelity environment model to directly provide vehicle updates. The approach is
an extension of a standard quadratic model that provides linear updates. The new
approach leverages information from the higher-order terms of the environment model
showing dramatic improvement over the standard method.
| Identifer | oai:union.ndltd.org:tamu.edu/oai:repository.tamu.edu:1969.1/ETD-TAMU-2010-12-8755 |
| Date | 2010 December 1900 |
| Creators | Brink, Kevin Michael |
| Contributors | Bhattacharyya, Shankar, Hurtado, John E. |
| Source Sets | Texas A and M University |
| Language | en_US |
| Detected Language | English |
| Type | thesis, text |
| Format | application/pdf |
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