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

机译:自适应决策机制,可以平衡多机器人团队的多个任务的执行

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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 behavior 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 behavior 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. (C) 2018 Elsevier B.V. All rights reserved.
机译:这项工作解决了多个机器人的协调问题,目的是在未知区域中找到特定的危险目标并进行协作处理。机器人系统的期望行为会带来多种需求,这也可能是矛盾的。本文将该问题作为约束的双目标优化问题提出,在该问题中,移动机器人必须执行两个特定的探索任务,并同时进行协作和协调才能解除危险目标的武装。这些目标是对立的目标,其中一个可能会受到支持,但只会损害另一个目标。因此,必须找到一个良好的权衡。为此目的,提出了一种自然启发性的方法和一个解析数学模型来解决考虑单个等效加权目标函数的这一问题。显示了在二维地形中模拟的拟议协调模型的结果,以评估拟议解决方案解决该问题的行为。我们分析了该方法的性能以及目标函数权重在不同条件下(静态和动态)的影响。在后一种情况下,在严格的有限能量预算或危险事件下,机器人可能会发生故障。本文最后对实验结果进行了严格的讨论。 (C)2018 Elsevier B.V.保留所有权利。

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