Thesis Type: Postgraduate
Institution Of The Thesis: Orta Doğu Teknik Üniversitesi, Faculty of Engineering, Department of Electrical and Electronics Engineering, Turkey
Approval Date: 2005
Student: MEHMETCAN APAYDIN
Co-Supervisor: İSMET ERKMEN, AYDAN MÜŞERREF ERKMENAbstract:
Making a robot autonomous has been a common challenge to be overcome since the very beginning. To be an autonomous system, the robot should collect environmental data, interpret them, and act accordingly. In order to accomplish these, some resource management should be conducted. That is, the resources, which are time, and computation power in our case, should be allocated to more important areas. Existing researches and approaches, however, are not always human like. Indeed they don̕t give enough importance on this. Starting from this point of view, the system proposed in this thesis supplies the resource management trying to be more ̕human like̕. It directs the focus of attention to where higher resolution algorithms are really needed. This ̕real need̕ is determined by the visual features of the scene, and current importance levels (or weight values) of each of these features. As a further attempt, the proposed system is compared with human subjects̕ characteristics. With unbiased subjects, a set of parameters which resembles a normal human is obtained. Then, in order to see the effect of the guidance, the subjects are asked to concentrate on a single predetermined feature. Finally, an artificial neural network based learning mechanism is added to learn to mimic a single human or a group of humans. The system can be used as a preattentive stage module, or some more feature channels can be introduced for better performance in the future.