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Cross-Entropy Optimization for Scaling Factors of a Fuzzy Controller: A See-and-Avoid Approach for Unmanned Aerial Systems

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Abstract

The Cross-Entropy (CE) is an efficient method for the estimation of rare-event probabilities and combinatorial optimization. This work presents a novel approach of the CE for optimization of a Soft-Computing controller. A Fuzzy controller was designed to command an unmanned aerial system (UAS) for avoiding collision task. The only sensor used to accomplish this task was a forward camera. The CE is used to reach a near-optimal controller by modifying the scaling factors of the controller inputs. The optimization was realized using the ROS-Gazebo simulation system. In order to evaluate the optimization a big amount of tests were carried out with a real quadcopter.

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Authors and Affiliations

  1. CAR - Centro de Automática y Robótica, Universidad Politécnica de Madrid, Madrid, Spain

    Miguel A. Olivares-Mendez, Pascual Campoy & Ignacio Mellado-Bataller

  2. Australian Research Centre for Aerospace Automation (ARCAA), Queensland University of Technology, GPO Box 2434, Brisbane, QLD, 4001, Australia

    Luis Mejias

Authors
  1. Miguel A. Olivares-Mendez
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  2. Luis Mejias
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  3. Pascual Campoy
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  4. Ignacio Mellado-Bataller
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Correspondence to Miguel A. Olivares-Mendez.

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Olivares-Mendez, M.A., Mejias, L., Campoy, P. et al. Cross-Entropy Optimization for Scaling Factors of a Fuzzy Controller: A See-and-Avoid Approach for Unmanned Aerial Systems. J Intell Robot Syst 69, 189–205 (2013). https://doi.org/10.1007/s10846-012-9791-5

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