Abstract
Technically, a group of more than two wheeled mobile robots working collectively towards a common goal are known as a multi-robot system. An increasing number of industries have implemented multi-robot systems to eliminate the risk of human injuries while working on hazardous tasks, and to improve productivity. Globally, engineers are continuously researching better, simple, and faster cooperative Control algorithms to provide a Control strategy where each agent in the robot formation can communicate effectively and achieve a consensus in their position, orientation and speed. This paper explores a novel Formation Building Algorithm and its global stability around a configuration vector. A simulation in MATLAB? was carried out to examine the performance of the Algorithm for two geometric formations and a fixed number of robots. In addition, an obstacle avoidance technique was presented assuming that all robots are equipped with range sensors. In particular, a uniform rounded obstacle is used to analyze the performance of the technique with the use of detailed geometric calculations.
Highlights
Multiple studies show that novel and better multi-agent formation algorithms have been proposed in recent years
The journal paper under review provides a powerful insight of a distributed control law, many other approaches have been explored throughout the history, such as the leader-follower or neural network approach
The journal article and this review proved that all robots will move parallel to the x-axis with a stabilizing control law with initial position ( xi (0), yi (0)) and a geometrical configuration vector denoted by = X1, X 2, X n,Y1,Y2,Yn where X n and Yn are constants
Summary
Multiple studies show that novel and better multi-agent formation algorithms have been proposed in recent years. The use of studies on basic motion dynamics in biology let us generate powerful algorithms to recreate geometric formations for groups of wheeled mobile vehicles [4]. In [9] the speed of each robot changes as in [10]; in this case, we use the average speed Algorithms such as in [11] study the Lyapunov method in detail to understand the system stability, here the non-holonomic motion model and energy equations are used to formulate the control dynamics of the system. The rationale behind the study and simulation of the Control Law is to provide a graphical representation of the geometrical formation, and to present an alternative to the Leader-Follower approach. In addition to the Control Law, this document presents an obstacle avoidance technique that seeks to evade a rounded obstacle while maintaining the formation
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