Yılansı robotyların üst seviye denetimi için bulanık eyleyici-eleştirici öğrenmeye dayalı akıllı denetleç


Tezin Türü: Yüksek Lisans

Tezin Yürütüldüğü Kurum: Orta Doğu Teknik Üniversitesi, Mühendislik Fakültesi, Elektrik ve Elektronik Mühendisliği Bölümü, Türkiye

Tezin Onay Tarihi: 2005

Tezin Dili: İngilizce

Öğrenci: Evrim Onur Arı

Danışman: İSMET ERKMEN

Özet:

In this thesis, an intelligent controller architecture for gait selection of a serpentine robot intended to be used in search and rescue tasks is designed, developed and simulated. The architecture is independent of the configuration of the robot and the robot is allowed to make different kind of movements, similar to grasping. Moreover, it is applicable to parallel processing in several aspects and it is an implementation of a controller network on robot segment network. In the architecture several behaviors are defined for each of the segments. Every behavior is realized in the form of Fuzzy Actor-Critic Learning agents based on fuzzy networks and reinforcement learning. Each segment controller determines the next suitable position in the sensory space acquired using ultrasound sensors, a genetic algorithm implementation then tries to find the change of the joint angles to achieve the desired movement in a given amount of time. This allows optimization on different criteria, during motion. Simulations are performed and presented to introduce the efficiency of the developed controller architecture. Moreover a simplified mathematical analysis is performed to gain insight of the controller dynamics.