Neural Network-based Genetic Algorithm for Autonomous Boat Pathfinding

Nur Hamid; Willy Dharmawan; Hidetaka Nambo

doi:10.1109/ICKII58656.2023.10332606

Neural Network-based Genetic Algorithm for Autonomous Boat Pathfinding

Nur Hamid^*, Willy Dharmawan, Hidetaka Nambo

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Genetic algorithms become widely used in various optimization as a nature-inspired algorithm. This biological-based algorithm includes three genetic operators: selection, crossover or recombination, and mutation. In this study, the genetic operator processed neural network parameters, including the weight and bias. Three-ray sensors with different directions input data into the neural network. We applied the method to autonomous boats for pathfinding responding to dynamic environment challenges. Generally, autonomous boats face difficulty in path-finding in dynamic environments. To evaluate the method, we experimented with the scenario of the static and dynamic environment (with wave surface) in a three-dimensional simulation platform. The hyperparameter of layer number and mutation rate variation were used. The results showed that the method was useful in pathfinding in static and dynamic environments.

Original language	English
Title of host publication	Proceedings of the 2023 IEEE 6th International Conference on Knowledge Innovation and Invention, ICKII 2023
Editors	Teen-Hang Meen
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	497-502
Number of pages	6
ISBN (Electronic)	9798350323535
DOIs	https://doi.org/10.1109/ICKII58656.2023.10332606
State	Published - 2023
Externally published	Yes
Event	6th IEEE International Conference on Knowledge Innovation and Invention, ICKII 2023 - Sapporo, Japan Duration: 11 Aug 2023 → 13 Aug 2023

Publication series

Name	Proceedings of the 2023 IEEE 6th International Conference on Knowledge Innovation and Invention, ICKII 2023

Conference

Conference	6th IEEE International Conference on Knowledge Innovation and Invention, ICKII 2023
Country/Territory	Japan
City	Sapporo
Period	11/08/23 → 13/08/23

Bibliographical note

Publisher Copyright:
© 2023 IEEE.

Keywords

autonomous boat
dynamic environment
genetic algorithm
neural network
pathfinding

ASJC Scopus subject areas

Computer Science Applications
Computer Vision and Pattern Recognition
Software
Decision Sciences (miscellaneous)
Information Systems and Management
Control and Systems Engineering
Control and Optimization
Artificial Intelligence

Access to Document

10.1109/ICKII58656.2023.10332606

Cite this

Hamid, N., Dharmawan, W., & Nambo, H. (2023). Neural Network-based Genetic Algorithm for Autonomous Boat Pathfinding. In T.-H. Meen (Ed.), Proceedings of the 2023 IEEE 6th International Conference on Knowledge Innovation and Invention, ICKII 2023 (pp. 497-502). (Proceedings of the 2023 IEEE 6th International Conference on Knowledge Innovation and Invention, ICKII 2023). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICKII58656.2023.10332606

Hamid, Nur ; Dharmawan, Willy ; Nambo, Hidetaka. / Neural Network-based Genetic Algorithm for Autonomous Boat Pathfinding. Proceedings of the 2023 IEEE 6th International Conference on Knowledge Innovation and Invention, ICKII 2023. editor / Teen-Hang Meen. Institute of Electrical and Electronics Engineers Inc., 2023. pp. 497-502 (Proceedings of the 2023 IEEE 6th International Conference on Knowledge Innovation and Invention, ICKII 2023).

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title = "Neural Network-based Genetic Algorithm for Autonomous Boat Pathfinding",

abstract = "Genetic algorithms become widely used in various optimization as a nature-inspired algorithm. This biological-based algorithm includes three genetic operators: selection, crossover or recombination, and mutation. In this study, the genetic operator processed neural network parameters, including the weight and bias. Three-ray sensors with different directions input data into the neural network. We applied the method to autonomous boats for pathfinding responding to dynamic environment challenges. Generally, autonomous boats face difficulty in path-finding in dynamic environments. To evaluate the method, we experimented with the scenario of the static and dynamic environment (with wave surface) in a three-dimensional simulation platform. The hyperparameter of layer number and mutation rate variation were used. The results showed that the method was useful in pathfinding in static and dynamic environments.",

keywords = "autonomous boat, dynamic environment, genetic algorithm, neural network, pathfinding",

author = "Nur Hamid and Willy Dharmawan and Hidetaka Nambo",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 6th IEEE International Conference on Knowledge Innovation and Invention, ICKII 2023 ; Conference date: 11-08-2023 Through 13-08-2023",

year = "2023",

doi = "10.1109/ICKII58656.2023.10332606",

language = "English",

series = "Proceedings of the 2023 IEEE 6th International Conference on Knowledge Innovation and Invention, ICKII 2023",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "497--502",

editor = "Teen-Hang Meen",

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address = "United States",

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Hamid, N , Dharmawan, W & Nambo, H 2023, Neural Network-based Genetic Algorithm for Autonomous Boat Pathfinding. in T-H Meen (ed.), Proceedings of the 2023 IEEE 6th International Conference on Knowledge Innovation and Invention, ICKII 2023. Proceedings of the 2023 IEEE 6th International Conference on Knowledge Innovation and Invention, ICKII 2023, Institute of Electrical and Electronics Engineers Inc., pp. 497-502, 6th IEEE International Conference on Knowledge Innovation and Invention, ICKII 2023, Sapporo, Japan, 11/08/23. https://doi.org/10.1109/ICKII58656.2023.10332606

Neural Network-based Genetic Algorithm for Autonomous Boat Pathfinding. / Hamid, Nur ; Dharmawan, Willy; Nambo, Hidetaka.
Proceedings of the 2023 IEEE 6th International Conference on Knowledge Innovation and Invention, ICKII 2023. ed. / Teen-Hang Meen. Institute of Electrical and Electronics Engineers Inc., 2023. p. 497-502 (Proceedings of the 2023 IEEE 6th International Conference on Knowledge Innovation and Invention, ICKII 2023).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Neural Network-based Genetic Algorithm for Autonomous Boat Pathfinding

AU - Hamid, Nur

AU - Dharmawan, Willy

AU - Nambo, Hidetaka

PY - 2023

Y1 - 2023

N2 - Genetic algorithms become widely used in various optimization as a nature-inspired algorithm. This biological-based algorithm includes three genetic operators: selection, crossover or recombination, and mutation. In this study, the genetic operator processed neural network parameters, including the weight and bias. Three-ray sensors with different directions input data into the neural network. We applied the method to autonomous boats for pathfinding responding to dynamic environment challenges. Generally, autonomous boats face difficulty in path-finding in dynamic environments. To evaluate the method, we experimented with the scenario of the static and dynamic environment (with wave surface) in a three-dimensional simulation platform. The hyperparameter of layer number and mutation rate variation were used. The results showed that the method was useful in pathfinding in static and dynamic environments.

AB - Genetic algorithms become widely used in various optimization as a nature-inspired algorithm. This biological-based algorithm includes three genetic operators: selection, crossover or recombination, and mutation. In this study, the genetic operator processed neural network parameters, including the weight and bias. Three-ray sensors with different directions input data into the neural network. We applied the method to autonomous boats for pathfinding responding to dynamic environment challenges. Generally, autonomous boats face difficulty in path-finding in dynamic environments. To evaluate the method, we experimented with the scenario of the static and dynamic environment (with wave surface) in a three-dimensional simulation platform. The hyperparameter of layer number and mutation rate variation were used. The results showed that the method was useful in pathfinding in static and dynamic environments.

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KW - dynamic environment

KW - genetic algorithm

KW - neural network

KW - pathfinding

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BT - Proceedings of the 2023 IEEE 6th International Conference on Knowledge Innovation and Invention, ICKII 2023

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Hamid N , Dharmawan W, Nambo H. Neural Network-based Genetic Algorithm for Autonomous Boat Pathfinding. In Meen TH, editor, Proceedings of the 2023 IEEE 6th International Conference on Knowledge Innovation and Invention, ICKII 2023. Institute of Electrical and Electronics Engineers Inc. 2023. p. 497-502. (Proceedings of the 2023 IEEE 6th International Conference on Knowledge Innovation and Invention, ICKII 2023). doi: 10.1109/ICKII58656.2023.10332606

Neural Network-based Genetic Algorithm for Autonomous Boat Pathfinding

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this