Investigation of Algorithms of Multi-Agent Robot Swarm Control in the Task of Finding the Shortest Path

In this paper, algorithms for multi-agent robot heap control are examined to address the task of finding the shortest path for each robot-agent. Three algorithms are considered: a common-sense-based method (COM), the particle cluster optimization method (PSO), and the ant algorithm (ACO). A mathematical model of the swarm of robots and agents was developed, and a modeling environment was created for testing and comparing the algorithms in terms of execution time and path length. The most efficient algorithm was then implemented on physical robots. Experimental results confirm the simulation data and demonstrate the practical applicability of the proposed algorithms in real scenarios.