Potential Field Method Parameters Tuning Using Fuzzy Inference System for Adaptive Formation Control of Multi-Mobile Robots
| Autor: | Hiroyuki Ishii, A. A. Abouelsoud, Ahmed M.R. Fathelbab, Basma Gh. Elkilany |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
0209 industrial biotechnology
Control and Optimization Computer science lcsh:Mechanical engineering and machinery Control (management) 02 engineering and technology formation control Field (computer science) obstacle avoidance 020901 industrial engineering & automation Artificial Intelligence Simplicity (photography) Obstacle avoidance 0202 electrical engineering electronic engineering information engineering lcsh:TJ1-1570 MATLAB computer.programming_language Mechanical Engineering Potential field Mobile robot Control engineering potential field method Robot 020201 artificial intelligence & image processing computer fuzzy inference system |
| Zdroj: | Robotics, Vol 9, Iss 1, p 10 (2020) Robotics Volume 9 Issue 1 |
| ISSN: | 2218-6581 |
| Popis: | Nowadays, employing more than one single robot in complex tasks or dangerous environments is highly required. Thus, the formation of multi-mobile robots is an active field. One famous method for formation control is the Potential Field Method due to its simplicity and efficiency in dynamic environments. Therefore, we propose a Fuzzy Inference tuning of the potential field parameters to overcome its limitations. We implement the modified method with tuned parameters on MATLAB and apply it to three TurtleBot3 burger model robots. Then, several real-time experiments are carried out to confirm the applicability and validity of the modified potential filed method to achieve the robots’ tasks. The results assert that the TurtleBot3 robots can escape from a local minimum, pass through a narrow passage, and pass between two closely placed obstacles. |
| Databáze: | OpenAIRE |
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