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


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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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).

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  • UAV
  • UAS
  • Fuzzy logic
  • Fuzzy control
  • Cross-Entropy
  • Visual servoing
  • Computer vision
  • Sense and avoid
  • See and avoid
  • Optimization