Model-based Bio-inspired Approaches for Ego-motion Estimation from Optical Flow

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Within the scope of the DFG-Projektakademie "Ingenieurwissenschaften", this project investigates bio-inspired approaches for robotic ego-motion estimation from optical flow. The novelty consists in an extension of efficient, but with respect to estimation quality sub-optimal, insect-eye vision with technical optimization approaches, in order to achieve computational efficiency, accuracy and robustness against disturbances, particularly, stochastical and time delay. Optimization approaches for integration with neuronal models are investigated and robustness of the complete system is evaluated analytically and experimentally. An assessment of the performance with autonomous mobile robots under real-world indoor and outdoor conditions is planned. WIthin the scope of the Projektakademie, this approach is firstly investigated for one-dimensional movements and in a later step generalized to six degrees of freedom within a successor project.