The University of Edinburgh -
Division of Informatics
Forrest Hill & 80 South Bridge

MSc Thesis #9848

Title:Guiding Evolution of Complex Robot Behaviours: Virtual Snesors and Task Decomposition
Date: 1998
Abstract:This project tackles issues of scalability and reality transfer in evolutionary robotics through the hard task of scoring goals in robot football.Evolutionary Robotics raison d'etre is to allow behavioural complexity beyond that imposed by the limitations of design, and as such scalability of techniques to more complex tasks is a central issue. The use of vision addresses sensory complexity and a novel technique of object level representation, using virtual sensors to provide such a description of the world, is implemented and seen to work. The use of task decomposition addresses task complexity, allowing division of a complete task into simpler sub-behaviours, making a potentially intractable problem tractable to solution by the evolutionary algorithm. Results show that designer misconceptions can reduce the efficacy of the latter approach.Good controllers were consistently evolved in simulation using genetic programming of logic-level controllers, and for the most part successfully transferred to reality. A controller that could score gols in a real-world environment using visual location of ball and goal was evolved. The complexity of this task, within evolutionary robotics work, goes some way to validating the scalability of the approaches.

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