| Abstract: |  In this work, methods for locomotion generation of modular robots are investigated. The main utilized locomotion methods are based on Central Pattern Generators (CPGs). We propose a novel method for automatic locomotion generation using Particle Swarm Optimization (PSO). The thesis describes how to use the PSO to learn locomotion for various configurations of modular robots and how to design the fitness function. Automatic generation of locomotion is used for gathering the locomotion primitives vocabulary for sampling-based motion planning methods. The proposed methods for locomotion generation as well as for motion planning are experimentally verified in a set of simulated scenarios.
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