|
Digital
Library of the European Council for Modelling
and Simulation |
Title: |
Blind Search Patterns For
Off-Line Path Planning |
Authors: |
Tarek
A. El-Mihoub, Christoph Tholen, Lars Nolle |
Published in: |
(2018). ECMS 2018
Proceedings Edited by: Lars Nolle, Alexandra Burger, Christoph Tholen, Jens
Werner, Jens Wellhausen European Council for Modeling and Simulation. doi: 10.7148/2018-0005 ISSN:
2522-2422 (ONLINE) ISSN:
2522-2414 (PRINT) ISSN:
2522-2430 (CD-ROM) 32nd European Conference on Modelling and
Simulation, Wilhelmshaven, Germany, May 22nd
– May 265h, 2018 |
Citation
format: |
Tarek
A. El-Mihoub, Christoph Tholen, Lars Nolle (2018). Blind Search Patterns For
Off-Line Path Planning, ECMS 2018
Proceedings Edited by: Lars Nolle, Alexandra Burger, Christoph Tholen, Jens
Werner, Jens Wellhausen European Council for Modeling and Simulation. doi: 10.7148/2018-0121 |
DOI: |
https://doi.org/10.7148/2018-0121 |
Abstract: |
Path planning is crucial for efficient
utilisation of autonomous underwater vehicles. The goal of the mission of an
autonomous underwater vehicle determines suitable strategies for path
planning. Blind search methods can be used for off-line path planning for
unknown environments to locate phenomena of interest. Different blind search
patterns have been implemented and evaluated in terms of their ability to
reach the mission’s goal. A novel blind search pattern that is based on a
truncated Lévy distribution is also proposed and compared with other search
patterns as path-planning algorithms. The simulations show that Lévy search pattern
can outperform other search patterns for small size phenomena. On the other
hand, the proposed inverse-Lévy pattern can locate large size phenomena more
than other search patterns. The simulations show that the probability of
locating the most important phenomenon by a single autonomous underwater
vehicle using blind search patterns is much smaller than of a swarm of
autonomous underwater vehicles in similar conditions. However, Lévy and
inverse-Lévy can be used for the worst-case scenario of no communication nor ability to use feedback information. |
Full
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