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Please use this identifier to cite or link to this item: https://dspace.lboro.ac.uk/2134/11136

Title: Optimization-based safety analysis of obstacle avoidance systems for unmanned aerial vehicles
Authors: Srikanthakumar, Sivaranjini
Liu, Cunjia
Chen, Wen-Hua
Keywords: Clearance process
Obstacle avoidance
Optimization
Potential field method
Unmanned aerial vehicle
Issue Date: 2012
Publisher: © Springer Science+Business Media B.V.
Citation: SRIKANTHAKUMAR, S., LIU, C. and CHEN, W-H, 2012. Optimization-based safety analysis of obstacle avoidance systems for unmanned aerial vehicles. Journal of Intelligent and Robotic Systems, 65 (1-4), pp. 219 - 231
Abstract: The integration of Unmanned Aerial Vehicles (UAVs) in airspace requires new methods to certify collision avoidance systems. This paper presents a safety clearance process for obstacle avoidance systems, where worst case analysis is performed using simulation based optimization in the presence of all possible parameter variations. The clearance criterion for the UAV obstacle avoidance system is defined as the minimum distance from the aircraft to the obstacle during the collision avoidance maneuver. Local and global optimization based verification processes are developed to automatically search the worst combinations of the parameters and the worst-case distance between the UAV and an obstacle under all possible variations and uncertainties. Based on a 6 Degree of Freedom (6DoF) kinematic and dynamic model of a UAV, the path planning and collision avoidance algorithms are developed in 3D space. The artificial potential field method is chosen as a path planning and obstacle avoidance candidate technique for verification study as it is a simple and widely used method. Different optimization algorithms are applied and compared in terms of the reliability and efficiency.
Description: This article was published in the Journal of Intelligent and Robotic Systems [© Springer Science+Business Media B.V.]. The definitive version is available at: http://link.springer.com/article/10.1007%2Fs10846-011-9586-0?LI=true#. The original publication is available at www.springerlink.com.
Version: Accepted for publication
DOI: 10.1007/s10846-011-9586-0
URI: https://dspace.lboro.ac.uk/2134/11136
Publisher Link: http://link.springer.com/article/10.1007%2Fs10846-011-9586-0?LI=true#
ISSN: 0921-0296
Appears in Collections:Published Articles (Aeronautical and Automotive Engineering)

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