Abstract
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.
| Original language | American English |
|---|---|
| Pages (from-to) | 319-324 |
| Number of pages | 6 |
| Journal | Proceedings of the 14th IEEE International Conference on Fuzzy Systems (2005, Reno, NV) |
| DOIs | |
| State | Published - Jan 1 2005 |
| Event | IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2005 - Reno, NV, United States Duration: May 22 2005 → May 25 2005 |
ASJC Scopus Subject Areas
- Software
- Theoretical Computer Science
- Artificial Intelligence
- Applied Mathematics
Keywords
- Robot control
- Mobile robots
- Navigation
- Fuzzy logic
- Neural networks
- Fuzzy systems
- Robot sensing systems
- Microcontrollers
- Microprocessors
- Random access memory
Disciplines
- Electrical and Computer Engineering
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