# Self-adaptive decision-making mechanisms to balance the execution of multiple tasks for a multi-robots team

## TL;DR

This paper proposes a self-adaptive, nature-inspired decision-making mechanism for multi-robot teams to balance exploration and cooperation tasks in hazardous environments, optimizing their coordination through a bi-objective model.

## Contribution

It introduces a novel analytical model and a weighted optimization approach for dynamic task balancing in multi-robot systems facing conflicting objectives.

## Key findings

- The proposed model effectively balances exploration and cooperation tasks.
- Performance varies with different weight configurations and environmental conditions.
- The approach demonstrates robustness under energy constraints and hazardous scenarios.

## Abstract

This work addresses the coordination problem of multiple robots with the goal of finding specific hazardous targets in an unknown area and dealing with them cooperatively. The desired behaviour for the robotic system entails multiple requirements, which may also be conflicting. The paper presents the problem as a constrained bi-objective optimization problem in which mobile robots must perform two specific tasks of exploration and at same time cooperation and coordination for disarming the hazardous targets. These objectives are opposed goals, in which one may be favored, but only at the expense of the other. Therefore, a good trade-off must be found. For this purpose, a nature-inspired approach and an analytical mathematical model to solve this problem considering a single equivalent weighted objective function are presented. The results of proposed coordination model, simulated in a two dimensional terrain, are showed in order to assess the behaviour of the proposed solution to tackle this problem. We have analyzed the performance of the approach and the influence of the weights of the objective function under different conditions: static and dynamic. In this latter situation, the robots may fail under the stringent limited budget of energy or for hazardous events. The paper concludes with a critical discussion of the experimental results.