Abstract
In this research, we examined a visual imitation algorithm on a group of real robots and analyzed the source of copying errors that are made by the robots visually learning by using this algorithm. As the two possible sources of the copying errors, the actuators of the demonstrator robot and the sensors of the learner robot were specified. First, it is calculated the amount and frequency of errors due to the actuators and we showed that errors due to actuators of the demonstrator robot were minimal. Second, it is examined the errors due to the sensors by using two different trajectory similarity metric in an experiment scenario and we discussed the origin of this kind of imitation error. In this way, we were able to model a source of behavioral diversity in a robot collective, which is similar to the natural systems, which results from errors that emerge during imitation activity.
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