|
Digital
Library of the European Council for Modelling
and Simulation |
Title: |
Informed
Search Patterns For Alleviating The Impact Of The Localisation Problem |
Authors: |
Tarek
El-Mihoub, Christoph Tholen, Lars Nolle |
Published in: |
(2019). ECMS 2019 Proceedings
Edited by: Mauro Iacono, Francesco Palmieri, Marco Gribaudo, Massimo Ficco,
European Council for Modeling and Simulation. DOI: http://doi.org/10.7148/2019 ISSN:
2522-2422 (ONLINE) ISSN:
2522-2414 (PRINT) ISSN:
2522-2430 (CD-ROM) 33rd International ECMS Conference on
Modelling and Simulation,
Caserta, Italy, June 11th – June 14th, 2019 |
Citation
format: |
Tarek El-Mihoub, Christoph Tholen, Lars
Nolle (2019). Informed Search Patterns For Alleviating The Impact Of The
Localisation Problem, ECMS 2019 Proceedings
Edited by: Mauro Iacono, Francesco Palmieri, Marco Gribaudo, Massimo Ficco
European Council for Modeling and Simulation. doi:
10.7148/2019-0037 |
DOI: |
https://doi.org/10.7148/2019-0037 |
Abstract: |
The efficiency
of locating a target by autonomous underwater vehicles (AUVs) depends on the
selected search strategy. The selected search strategy should take into
consideration all aspects of the nature and the behaviour of the search
agent, which executes the search. It should also take into account the nature
of the search environment. The long-term goal of this research is to use a
small cooperative swarm of AUVs to locate a phenomenon of interest in a
predefined marine environment. In this paper, some characteristics of search
models that can promote constructive collaboration between AUVs for effective
search are discussed. Two heuristic algorithms to locate a target are
proposed. These heuristics do not use the exact location of the AUV to decide
on the next search action as a mean to alleviate the impact of the
localisation problem. The two heuristics outperform blind search algorithms in
a search environment with two targets of different priorities. The impact of the
localisation problem is considered by evaluating the performance of the
algorithms in the presence of localisation errors. The results show that one
of the proposed informed search heuristics is able to improve the search
performance even in the presence of localisation errors. |
Full
text: |