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This study aims to apply Artificial Immune Systems (AIS) to a mobile robot making it capable of traversing an unknown environment and mapping it while looking for the target. We have implemented a mixture of AntibodyAntibody (AbAb) interaction algorithm coupled with negative selection algorithms to develop the proposed AIS controller. We have also developed a method for random generation of antibodies to make the system more similar to the actual biological process. Finally, a generalized architecture for representation of antibodies and antigens in a standard mobile robot using proximity sensors for interaction with the environment has been introduced. The results show that the proposed algorithm was able to explore the unknown environments while learning from past behavior and look for the target. It was also able to successfully map the traversed path and plot the obstacles based on their type.
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