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EnglishIn this paper, a new three-dimensional path planning approach with obstacle avoidance for UAVs is proposed. The aim is to provide a computationally-fast on-board sub-optimal solution for collision- free path planning in static environments. The optimal 3D path is an NP (non-deterministic polynomial-time) hard problem which may be solved numerically by global optimization algorithms such as the Particle Swarm Optimization (PSO). Application of PSO to the 3D path plan- ning class of problems faces typical challenges such slow convergence rate. It is shown that the performance may be improved markedly by imple- menting a novel parallel approach and incorporation of new termination conditions. Moreover, the exploration and exploitation parameters are optimized to nd a reasonably short, smooth, and safe path connecting the way-points. As an additional precaution to avoid collisions, obstacle dimensions are artificially slightly enlarged. To verify the robustness of the algorithm, several simulations are carried out by varying the num- ber of obstacles, their volume, and location in space. A certain number of simulations exploiting the random nature of PSO are performed to highlight the computational efficiency and the robustness of this new approach.
A 3D Path Planning Algorithm based on PSO for Autonomous UAVs Navigation: 9th International Conference, BIOMA 2020, Brussels, Belgium, November 19–20, 2020, Proceedings / Mirshamsi, Alireza; Godio, Simone; Nobakhti, Amin; Primatesta, Stefano; Dovis, Fabio; Guglieri, Giorgio. - ELETTRONICO. - 12438(2020).
| Titolo: | A 3D Path Planning Algorithm based on PSO for Autonomous UAVs Navigation: 9th International Conference, BIOMA 2020, Brussels, Belgium, November 19–20, 2020, Proceedings |
| Autori: | |
| Data di pubblicazione: | 2020 |
| Titolo del libro: | Bioinspired Optimization Methods and Their Applications |
| Serie: | |
| Abstract: | In this paper, a new three-dimensional path planning approach with obstacle avoidance for UAVs is... proposed. The aim is to provide a computationally-fast on-board sub-optimal solution for collision- free path planning in static environments. The optimal 3D path is an NP (non-deterministic polynomial-time) hard problem which may be solved numerically by global optimization algorithms such as the Particle Swarm Optimization (PSO). Application of PSO to the 3D path plan- ning class of problems faces typical challenges such slow convergence rate. It is shown that the performance may be improved markedly by imple- menting a novel parallel approach and incorporation of new termination conditions. Moreover, the exploration and exploitation parameters are optimized to nd a reasonably short, smooth, and safe path connecting the way-points. As an additional precaution to avoid collisions, obstacle dimensions are artificially slightly enlarged. To verify the robustness of the algorithm, several simulations are carried out by varying the num- ber of obstacles, their volume, and location in space. A certain number of simulations exploiting the random nature of PSO are performed to highlight the computational efficiency and the robustness of this new approach. |
| ISBN: | 978-3-030-63709-5 |
| Appare nelle tipologie: | 2.1 Contributo in volume (Capitolo o Saggio) |
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| File | Descrizione | Tipologia | Licenza | |
|---|---|---|---|---|
| BIOMA_final_paper_1.zip | File zip contenente tutti i documenti Latex | Altro materiale allegato | Non Pubblico - Accesso privato/ristretto | Administrator Richiedi una copia |
| Paper.pdf | 2. Post-print / Author's Accepted Manuscript | PUBBLICO - Tutti i diritti riservati | Embargo: 29/10/2021 Richiedi una copia | |
| 496171_1_En_21_Chapter_Author.pdf | 2a Post-print versione editoriale / Version of Record | Non Pubblico - Accesso privato/ristretto | Administrator Richiedi una copia |
http://hdl.handle.net/11583/2850165
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