Concept and design for a swarm robot and implementation of the collaboration algorithm

Abstract

With the continuous advancement of technology, collaborative robots in artificial intelligence have seen a very important and rapid development due to their use in all domains, especially in hostile, dangerous, and hard-to-reach environments where many robots are designed to perform jobs that are dangerous to humans. Several studies have made progress in this domain using various artificial intelligence algorithms. In this paper, we highlight two important algorithms and apply them to a group of robots in different challenging environments based on the Gazebo simulator. The first algorithm is the Search-Based Planning Library (SBPL) algorithm, and the second is the A-star algorithm, and we compare them. The experimental results showed that both algorithms are suitable, but the A-star algorithm is best suited for robots to cooperate with each other to reach the targets without hitting obstacles in the shortest time compared to the SBPL algorithm because making the right decision will take a lot of time.