Abstract
Localization techniques involve estimating the robot’s pose and uncertainty with respect to a world map by making use of sensors available on the robotic platform being used. Using the camera as a sensor involves preprocessing images to get range and bearing measurements of landmarks visible in the image with respect to the local frame of the camera. In this paper we explore template matching, phase correlation and contour based marker detection methods as preprocessors for landmark extraction for the localization problem. We compare performance of the three methods by embedding them in a Kalman filter framework running on a simulated quadrotor in V-REP.
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Raj, A.N.J., Chawla, A., Sridhar, G., Akshay, D. (2018). A Comparative Study of Preprocessing Techniques for Marker Based Localization in UAVs. In: Abraham, A., Cherukuri, A., Madureira, A., Muda, A. (eds) Proceedings of the Eighth International Conference on Soft Computing and Pattern Recognition (SoCPaR 2016). SoCPaR 2016. Advances in Intelligent Systems and Computing, vol 614. Springer, Cham. https://doi.org/10.1007/978-3-319-60618-7_41
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DOI: https://doi.org/10.1007/978-3-319-60618-7_41
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