Grey Wolf Optimization-Based Decision-Control for Multi-Robot Signal Source Localization in Communication-Constrained Environments

Abstract

By developing and evaluating a decision-control strategy using an Hazardous Environment method, this study addresses the issue of signal source localization utilizing a group of autonomous robots. A new grouping technique is the basis of our proposed algorithm, Optimal Weighting Grey Wolf Optimization. The OW-GWO algorithm takes into account the past, present, and future ideal positions of all grey wolves, ranks them according to these positions, and updates these positions as needed. The alpha wolf constantly estimates where the prey is, and the rest of the grey wolves follow suit. Integrating the OWGWO method with an enhanced grouping strategy and dividing the algorithm into two stages—the random walk stage with the dynamic grouping stage—allows us to address the multi-target issue of swarm robots search. In the random walk phase, grey wolves adjust their best placements based on history and travel at random. The OWGWO algorithm builds search auxiliary points throughout the dynamic grouping stage by using a better grouping approach that takes into account the previous ideal placements of individual grey wolves. In order to hunt for various prey, grey wolves use these to form groups. . A decision level along with a control level are both included in the proposed decision-control method. The decision level employs a particle filter to make educated guesses about where the signal could be coming from. The actual location of the signal source becomes closer to the predicted position as the robots move. At the level of control, a consensus controller is suggested for commanding several robots to locate a signal source according to the predicted location of the source. Additionally, in order to alleviate some of the communication load, an Hazardous Environment mechanism is developed. Lastly, experiments and simulations demonstrate that the suggested decision-control method using the Hazardous Environment strategy solves the signal source localization issue well.