Abstract
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.
Highlights
The multi-robot system is more robust, reliable, and precise than a single robot [1,2]
We test the applicability of the modified Potential Field Method (PFM) with the tuned parameters using
We aim to illustrate how the Fuzzy Inference System (FIS) tuning of the Potential Field (PF) parameters solves some of the limitations of the traditional PFM such as oscillating near narrow passages or near closely placed obstacles
Summary
The multi-robot system is more robust, reliable, and precise than a single robot [1,2]. One of the main problems in the multi-robot system is the formation control. The formation of the multi-robot system is a cooperative behavior of the interacting mobile robots sharing one goal [4]. Lots of research studies have been presented in this field. Some of these researchers depend on a central controller such as [5,6,7]. These methods are very prone to failure. They are not suitable for the formation problem [8]. Decentralized formation control methods are suggested such as the Potential Field Method (PFM) [9]
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