Applying KIV dynamic neural network model for real time navigation by mobile robot EMMA

We use a biologically inspired dynamic neural network model to accomplish goal-oriented navigation by a mobile robot in a real environment with obstacles. This model is the KIV model of the brain. Real time navigation is a challenging task, especially when there is no a priori information about the environment. Our robot EMMA is designed to be autonomous using various sensory inputs, which are integrated to achieve an efficient navigation task. This paper focuses on the design, implementation, and evaluation of the performance of EMMA and gives a proof-of-principle in a real environment.