Fuzzy actor-critic learning based intelligent controller for high-level motion control of serpentine robots

Arı, Evrim Onur
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.


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Image segmentation is an important research area in digital image processing with several applications in vision-guided autonomous robotics, product quality inspection, medical diagnosis, the analysis of remotely sensed images, etc. The aim of image segmentation can be defined as partitioning an image into homogeneous regions in terms of the features of pixels extracted from the image. Image segmentation methods can be classified into four main categories: 1) clustering methods, 2) region-based methods, 3) ...
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Citation Formats
E. O. Arı, “Fuzzy actor-critic learning based intelligent controller for high-level motion control of serpentine robots,” M.S. - Master of Science, Middle East Technical University, 2005.