Fuzzy controlled adaptive follow the gap obstacle avoidance algorithm

Bilal Yucel; Abdurrahman Yilmaz; Osman Ervan; Hakan Temeltas

doi:10.1145/3505688.3505704

Fuzzy controlled adaptive follow the gap obstacle avoidance algorithm

Bilal Yucel^*, Abdurrahman Yilmaz, Osman Ervan, Hakan Temeltas

^*Corresponding author for this work

Department of Control and Automation Engineering

Istanbul Technical University

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

Abstract

Follow the Gap Method (FGM) and Improved Follow the Gap Method (FGM-I) are geometric obstacle avoidance algorithms for navigation. In these methods, the vehicle detects the gaps around the object and navigates to the midpoint of the optimal gap calculated according to a defined function. One missing point of these algorithms is failure to the goal point when there is an obstacle near to it. Another drawback is that early consideration of obstacles causes long trajectories. In this paper, Adaptive Follow the Gap (A-FGM) is presented to overcome these two points. In A-FGM, a fuzzy controlled evaluation radius is set and only obstacles within this region are included in the evaluation. A differential drive robot is used in simulations and results show that A-FGM increases the success rate of reaching the goal and efficiency of previous algorithms. The source code of the developed approach is shared on GitHub 1.

Original language	English
Title of host publication	ICRAI 2021 - 2021 7th International Conference on Robotics and Artificial Intelligence
Publisher	Association for Computing Machinery
Pages	93-98
Number of pages	6
ISBN (Electronic)	9781450385855
DOIs	https://doi.org/10.1145/3505688.3505704
Publication status	Published - 19 Nov 2021
Event	7th International Conference on Robotics and Artificial Intelligence, ICRAI 2021 - Guangzhou, China Duration: 19 Nov 2021 → 22 Nov 2021

Publication series

Name	ACM International Conference Proceeding Series

Conference

Conference	7th International Conference on Robotics and Artificial Intelligence, ICRAI 2021
Country/Territory	China
City	Guangzhou
Period	19/11/21 → 22/11/21

Bibliographical note

Publisher Copyright:
© 2021 ACM.

Keywords

Adaptive Control
Fuzzy Control
Mobile Robots
Obstacle Avoidance
Path Planning
Robot Navigation

Access to Document

10.1145/3505688.3505704

Cite this

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title = "Fuzzy controlled adaptive follow the gap obstacle avoidance algorithm",

abstract = "Follow the Gap Method (FGM) and Improved Follow the Gap Method (FGM-I) are geometric obstacle avoidance algorithms for navigation. In these methods, the vehicle detects the gaps around the object and navigates to the midpoint of the optimal gap calculated according to a defined function. One missing point of these algorithms is failure to the goal point when there is an obstacle near to it. Another drawback is that early consideration of obstacles causes long trajectories. In this paper, Adaptive Follow the Gap (A-FGM) is presented to overcome these two points. In A-FGM, a fuzzy controlled evaluation radius is set and only obstacles within this region are included in the evaluation. A differential drive robot is used in simulations and results show that A-FGM increases the success rate of reaching the goal and efficiency of previous algorithms. The source code of the developed approach is shared on GitHub 1.",

keywords = "Adaptive Control, Fuzzy Control, Mobile Robots, Obstacle Avoidance, Path Planning, Robot Navigation",

author = "Bilal Yucel and Abdurrahman Yilmaz and Osman Ervan and Hakan Temeltas",

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year = "2021",

month = nov,

day = "19",

doi = "10.1145/3505688.3505704",

language = "English",

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Yucel, B, Yilmaz, A, Ervan, O & Temeltas, H 2021, Fuzzy controlled adaptive follow the gap obstacle avoidance algorithm. in ICRAI 2021 - 2021 7th International Conference on Robotics and Artificial Intelligence. ACM International Conference Proceeding Series, Association for Computing Machinery, pp. 93-98, 7th International Conference on Robotics and Artificial Intelligence, ICRAI 2021, Guangzhou, China, 19/11/21. https://doi.org/10.1145/3505688.3505704

Fuzzy controlled adaptive follow the gap obstacle avoidance algorithm. / Yucel, Bilal; Yilmaz, Abdurrahman; Ervan, Osman et al.
ICRAI 2021 - 2021 7th International Conference on Robotics and Artificial Intelligence. Association for Computing Machinery, 2021. p. 93-98 (ACM International Conference Proceeding Series).

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

TY - GEN

T1 - Fuzzy controlled adaptive follow the gap obstacle avoidance algorithm

AU - Yucel, Bilal

AU - Yilmaz, Abdurrahman

AU - Ervan, Osman

AU - Temeltas, Hakan

PY - 2021/11/19

Y1 - 2021/11/19

N2 - Follow the Gap Method (FGM) and Improved Follow the Gap Method (FGM-I) are geometric obstacle avoidance algorithms for navigation. In these methods, the vehicle detects the gaps around the object and navigates to the midpoint of the optimal gap calculated according to a defined function. One missing point of these algorithms is failure to the goal point when there is an obstacle near to it. Another drawback is that early consideration of obstacles causes long trajectories. In this paper, Adaptive Follow the Gap (A-FGM) is presented to overcome these two points. In A-FGM, a fuzzy controlled evaluation radius is set and only obstacles within this region are included in the evaluation. A differential drive robot is used in simulations and results show that A-FGM increases the success rate of reaching the goal and efficiency of previous algorithms. The source code of the developed approach is shared on GitHub 1.

AB - Follow the Gap Method (FGM) and Improved Follow the Gap Method (FGM-I) are geometric obstacle avoidance algorithms for navigation. In these methods, the vehicle detects the gaps around the object and navigates to the midpoint of the optimal gap calculated according to a defined function. One missing point of these algorithms is failure to the goal point when there is an obstacle near to it. Another drawback is that early consideration of obstacles causes long trajectories. In this paper, Adaptive Follow the Gap (A-FGM) is presented to overcome these two points. In A-FGM, a fuzzy controlled evaluation radius is set and only obstacles within this region are included in the evaluation. A differential drive robot is used in simulations and results show that A-FGM increases the success rate of reaching the goal and efficiency of previous algorithms. The source code of the developed approach is shared on GitHub 1.

KW - Adaptive Control

KW - Fuzzy Control

KW - Mobile Robots

KW - Obstacle Avoidance

KW - Path Planning

KW - Robot Navigation

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M3 - Conference contribution

AN - SCOPUS:85128631967

T3 - ACM International Conference Proceeding Series

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EP - 98

BT - ICRAI 2021 - 2021 7th International Conference on Robotics and Artificial Intelligence

PB - Association for Computing Machinery

T2 - 7th International Conference on Robotics and Artificial Intelligence, ICRAI 2021

Y2 - 19 November 2021 through 22 November 2021

ER -

Fuzzy controlled adaptive follow the gap obstacle avoidance algorithm

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Bibliographical note

Keywords

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