Abstract
In this paper, we propose a new Decomposition-Coordination Method (DCM) to solve the nonlinear problem of optimal path planning, for autonomous Unmanned Aerial Vehicle (UAV) in a dynamic environment. The main objective of this work is to enable safe autonomous navigation to the UAV. Our algorithm of decomposition-coordination computes initially an optimal path leading to the desired position, and according to the information supplied by a deciding unit, the UAV can predict the potential collisions, and avoid them by computing new collision-free paths if needed, allowing more reactivity to the UAV. This approach consists of first, choosing a suitable mathematical model that depicts the dynamics of the UAV, to which we associate the objective functions to end up with a multi-objective optimization problem. We proceed then to the resolution of the nonlinear system, by subdividing it into a set of smaller interconnected subsystems. The DCM is then used to achieve a local treatment of the non-linearity and reduce the processing time, where each subsystem is split between two levels for parallel processing, and the coordination is ensured after the resolution of the system using the method of Lagrange multipliers. We study as well the convergence and the stability of the algorithm, then we present the results of our simulation on Matlab to corroborate the potential of this theoretical method.
Supported by the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement No 777720.
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Nizar, I., Illoussamen, Y., Illoussamen, E.H., Mestari, M. (2020). Safe and Optimal Path Planning for Autonomous UAV Using a Decomposition-Coordination Method. In: Hamlich, M., Bellatreche, L., Mondal, A., Ordonez, C. (eds) Smart Applications and Data Analysis. SADASC 2020. Communications in Computer and Information Science, vol 1207. Springer, Cham. https://doi.org/10.1007/978-3-030-45183-7_21
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