TY - JOUR
T1 - Potential field method parameters tuning using fuzzy inference system for adaptive formation control of multi-mobile robots
AU - Elkilany, Basma Gh
AU - Abouelsoud, A. A.
AU - Fathelbab, Ahmed M.R.
AU - Ishii, Hiroyuki
N1 - Funding Information:
Funding: This research is funded by the Ministry of Higher Education.
Funding Information:
This research is funded by the Ministry of Higher Education. The authors would like to thank the Egypt-Japan University of Science and Technology (EJUST) for continuous help and support.
Publisher Copyright:
© 2020 by the authors.
PY - 2020/3/1
Y1 - 2020/3/1
N2 - 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.
AB - 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.
KW - Formation control
KW - Fuzzy inference system
KW - Obstacle avoidance
KW - Potential field method
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U2 - 10.3390/robotics9010010
DO - 10.3390/robotics9010010
M3 - Article
AN - SCOPUS:85082421885
SN - 2218-6581
VL - 9
JO - Robotics
JF - Robotics
IS - 1
M1 - 10
ER -