Neuro-fuzzy mobile robot navigation
Added Title
IEEE International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management (10th : 2018)
HNICEM 2018
College
Gokongwei College of Engineering
Department/Unit
Manufacturing Engineering and Management
Document Type
Conference Proceeding
Source Title
2018 IEEE 10th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management, HNICEM 2018
Publication Date
3-12-2019
Abstract
In mobile robot navigation, it is fundamental to have goal seeking and obstacle avoidance in the navigation algorithm. In this paper neural networks are used to learn both goal seeking and obstacle avoidance from a dataset generated by two different fuzzy logic navigation algorithms. The neural network was able to learn from both algorithms and produce a smoother path than the two. Additionally, a neural network was able to learn how to escape a concave obstacle.
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Digitial Object Identifier (DOI)
10.1109/HNICEM.2018.8666348
Recommended Citation
Tan Ai, R. C., & Dadios, E. P. (2019). Neuro-fuzzy mobile robot navigation. 2018 IEEE 10th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management, HNICEM 2018 https://doi.org/10.1109/HNICEM.2018.8666348
Disciplines
Manufacturing
Keywords
Fuzzy logic; Mobile robots; Motion control devices
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