A behavior based robot control system architecture for navigation environments with randomly allocated walls

Altuntaş, Berrin
Integration of knowledge to the control system of a robot is the best way to emerge intelligence to robot. The most useful knowledge for a robot control system that aims to visit the landmarks in an environment is the enviromental knowledge. The most natural representation of the robot2s environment is a map. This study presents a behavior based robot control system architecture that is based on subsumption and motor schema architectures and enables the robot to construct the map of the environment by using proximity sensors, odometry sensors, compass and image. The knowledge produced after processing the sensor values, is stored in Short Term Memory (STM) or Long Term Memory (LTM) of the robot, according to the persistence requirements of the knowledge. The knowledge stored in the STM acts as a sensor value, while LTM stores the map of the environment. The map of the environment is not a priori information for the robot, but it constructs the map as it moves in the environment. By the help of the map constructed the robot will be enabled to visit non-visited areas in the environment and to localize itself in its internal world. The controller is designed for a real robot Khepera equipped with the sensors required. The controller was tested on simulator called Webots version 2.0 on Linux operating system.


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Citation Formats
B. Altuntaş, “A behavior based robot control system architecture for navigation environments with randomly allocated walls,” M.S. - Master of Science, Middle East Technical University, 2003.