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Publication - Professor Walterio Mayol-Cuevas

    Predicting Micro Air Vehicle landing behaviour from visual texture

    Citation

    Bartholomew, J, Calway, A & Mayol-Cuevas, W, 2012, ‘Predicting Micro Air Vehicle landing behaviour from visual texture’. in: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE Computer Society, pp. 4550-4556

    Abstract

    We introduce a framework to predict the landing behaviour of a Micro Air Vehicle (MAV) from the appearance of the landing surface. We approach this problem by learning a mapping from visual texture observed from an onboard camera to the landing behaviour on a set of sample materials. In this case we exemplify our framework by predicting the yaw angle of the MAV after landing. Our framework demonstrates the applicability of established texture classification methods usually tested on stationary camera setups for the more challenging case of textures observed from a MAV. Results for supervised training demonstrate good estimation of the landing behaviour and motivate future work to implement autonomous decision making strategies and other behaviour predictions based on imagery.

    Full details in the University publications repository