Monocular visual-inertial SLAM-based collision avoidance strategy for fail-safe UAV using fuzzy logic controllers

Fu, Changhong and Olivares Mendez, Miguel Ángel and Suarez Fernandez, Ramon and Campoy Cervera, Pascual (2014). Monocular visual-inertial SLAM-based collision avoidance strategy for fail-safe UAV using fuzzy logic controllers. "Journal of intelligent & robotic systems", v. 73 (n. 1); pp. 513-533. ISSN 0921-0296. https://doi.org/10.1007/s10846-013-9918-3.

Description

Title: Monocular visual-inertial SLAM-based collision avoidance strategy for fail-safe UAV using fuzzy logic controllers
Author/s:
  • Fu, Changhong
  • Olivares Mendez, Miguel Ángel
  • Suarez Fernandez, Ramon
  • Campoy Cervera, Pascual
Item Type: Article
Título de Revista/Publicación: Journal of intelligent & robotic systems
Date: January 2014
ISSN: 0921-0296
Volume: 73
Subjects:
Freetext Keywords: Monocular visual-inertial SLAM Collision avoidance Fuzzy Logic Controller (FLC) Cross Entropy Optimization (CEO) Unmanned Aerial Vehicle (UAV)
Faculty: Centro de Automática y Robótica (CAR) UPM-CSIC
Department: Otro
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

In this paper, we developed a novel Cross-Entropy Optimization (CEO)-based Fuzzy Logic Controller (FLC) for Fail-Safe UAV to expand its collision avoidance capabilities in the GPS-denied envrionments using Monocular Visual-Inertial SLAM-based strategy. The function of this FLC aims to control the heading of Fail-Safe UAV to avoid the obstacle, e.g. wall, bridge, tree line et al, using its real-time and accurate localization information. In the Matlab Simulink-based training framework, the Scaling Factor (SF) is adjusted according to the collision avoidance task firstly, and then the Membership Function (MF) is tuned based on the optimized Scaling Factor to further improve the control performances. After obtained the optimal SF and MF, 64% of rules has been reduced (from 125 rules to 45 rules), and a large number of real see-and-avoid tests with a quadcopter have done. The simulation and experiment results show that this new proposed FLC can precisely navigates the Fail-Safe UAV to avoid the obstacle, obtaining better performances compared to only SF optimization-based FLC. To our best knowledge, this is the first work to present the optimized FLC using Cross-Entropy method in both SF and MF optimization, and apply it in the UAV.

More information

Item ID: 36248
DC Identifier: http://oa.upm.es/36248/
OAI Identifier: oai:oa.upm.es:36248
DOI: 10.1007/s10846-013-9918-3
Official URL: https://link.springer.com/article/10.1007/s10846-013-9918-3
Deposited by: Memoria Investigacion
Deposited on: 01 Apr 2017 08:25
Last Modified: 01 Apr 2017 08:25
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