Victim Position Detection Using Swarm Robots

Abstract

This paper examines the scenario of a swarm of robots in the aftermath of a disaster. In the field of swarm robotics, a group of individual and relatively simple robots collaboratively work towards a common objective through local communication and diverse control strategies. As these robots engage with their environment or with one another, the primary goal is to establish effective collaborative behaviour. For search and rescue operations, swarm robots play a key role in sensing and sharing information within themselves very effectively. A practical real-life application for this example is, It is used in solving nonlinear optimization problems. Finding the victim’s location during a search and rescue operation is similar to the best solution that we find while performing linear optimization problem. The robot which finds the victim with the best position is referred to as the master robot, and the rest as slave robots. These roles can change at any point during the mission based on the new information. The collaborative behaviour of the robots makes it easier to locate the victim more effectively. The efficacy and optimality of suggested approach has been evaluated on a number of common benchmark functions. Simulation results demonstrate that the proposed methods effectively locate the victim while exhibiting variations in exploration efficiency. The comparative analysis clearly shows the strengths and limitations of each algorithm in dynamic search environments.