NAO robot fuzzy obstacle avoidance in virtual environment

The fuzzy inference system for obstacle avoidance developed in this paper is designed for NAO humanoid robot. The fuzzy obstacle avoidance (Fuzzy OA) has been tested in Webots virtual environment and the results showed that this method is almost two times faster than the Naoqi framework obstacle avoidance (Naoqi OA) while the robot is much more stable. Because the fuzzy inference system is a method that relies on trial an error and experience, the obstacle avoidance algorithm is subject to improvements. Future developments will take into account these results and will add other fuzzy inference systems for navigation, in order to get more autonomy for Nao robot.

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Publication Details

Journal
Periodicals of Engineering and Natural Sciences (PEN)
Published
2025-12-31
DOI
https://doi.org/10.21533/pen.v7.i1.1498
Primary Topic
Robotic Path Planning Algorithms
Type
article
Field-Weighted Citation Impact
0.00

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article

NAO robot fuzzy obstacle avoidance in virtual environment

Alexandru Gal, Octavian Daniel Melinte, Luige Vlădăreanu
Periodicals of Engineering and Natural Sciences (PEN)
Robotic Path Planning Algorithms
article

NAO robot fuzzy obstacle avoidance in virtual environment

Alexandru Gal, Octavian Daniel Melinte, Luige Vlădăreanu
article en

Abstract

The fuzzy inference system for obstacle avoidance developed in this paper is designed for NAO humanoid robot. The fuzzy obstacle avoidance (Fuzzy OA) has been tested in Webots virtual environment and the results showed that this method is almost two times faster than the Naoqi framework obstacle avoidance (Naoqi OA) while the robot is much more stable. Because the fuzzy inference system is a method that relies on trial an error and experience, the obstacle avoidance algorithm is subject to improvements. Future developments will take into account these results and will add other fuzzy inference systems for navigation, in order to get more autonomy for Nao robot.

Periodicals of Engineering and Natural Sciences (PEN)Vol. 7(1)
European Commission, Academia Româna, Unitatea Executiva pentru Finantarea Invatamantului Superior, a Cercetarii, Dezvoltarii si Inovarii, Horizon 2020 Framework Programme, Colegiul Consultativ pentru Cercetare-Dezvoltare şi Inovare
Openalex Percentile: Top 34%
Robotic Path Planning Algorithms
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