A reactive fuzzy logic based control strategy was developed for mobile robot navigation. To decrease the number of fuzzy rules and related processing, a RAM-based neural network was combined with the fuzzy logic strategy. The fuzzy rules are used to interpret sensor information. The neural network uses results from the fuzzy logic as well as environmental information to make navigation decisions. The feasibility of this neuro-fuzzy approach was demonstrated on a mobile robot using a simple, 8-bit microcontroller. Experiments show the approach works well, as the robot was able to successfully avoid objects while seeking a goal in real-time. The neuro-fuzzy approach is code-efficient, fast, and easy to relate to the physical world.
N. Zhang et al., "An Embedded Real-Time Neuro-Fuzzy Controller for Mobile Robot Navigation," Proceedings of the 14th IEEE International Conference on Fuzzy Systems (2005, Reno, NV), Institute of Electrical and Electronics Engineers (IEEE), Jan 2005.
The definitive version is available at https://doi.org/10.1109/FUZZY.2005.1452413
14th IEEE International Conference on Fuzzy Systems, FUZZ '05 (2005: May 25, Reno, NV)
Electrical and Computer Engineering
Keywords and Phrases
Robot control; Mobile robots; Navigation; Fuzzy logic; Neural networks; Fuzzy systems; Robot sensing systems; Microcontrollers; Microprocessors; Random access memory
International Standard Serial Number (ISSN)
Article - Conference proceedings
© 2005 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.
01 Jan 2005