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A Bio-inspired Approach for Collaborative Exploration with Mobile Battery Recharging in Swarm Robotics

机译:群体机器人中移动电池充电的协作探索生物启发方法

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Swarm Robotics are widely conceived as the development of new computationally efficient tools and techniques aimed at easing and enhancing the coordination of multiple robots towards collaboratively accomplishing a certain mission or task. Among the different criteria under which the performance of Swarm Robotics can be gauged, energy efficiency and battery lifetime have played a major role in the literature. However, technological advances favoring power transfer among robots have unleashed new paradigms related to the optimization of the battery consumption considering it as a resource shared by the entire swarm. This work focuses on this context by elaborating on a routing problem for collaborative exploration in Swarm Robotics, where a subset of robots is equipped with battery recharging functionalities. Formulated as a bi-objective optimization problem, the quality of routes is measured in terms of the Pareto trade-off between the predicted area explored by robots and the risk of battery outage in the swarm. To efficiently balance these conflicting two objectives, a bio-inspired evolutionary solver is adopted and put to practice over a realistic experimental setup implemented in the VREP simulation framework. Obtained results elucidate the practicability of the proposed scheme, and suggest future research leveraging power transfer capabilities over the swarm.
机译:Swarm Robotics被广泛认为是新的计算效率高的工具和技术的开发,旨在减轻和增强多个机器人的协调性,以协同完成某项任务或任务。在衡量Swarm Robotics性能的不同标准中,能效和电池寿命在文献中起着重要作用。但是,支持机器人之间进行动力传输的技术进步已经释放了与电池消耗优化相关的新范例,将电池消耗视为整个群体共享的资源。这项工作的重点是通过详细说明Swarm机器人技术中用于协作探索的路由问题,该机器人的子集配备了电池充电功能。路线的质量被表述为双目标优化问题,它是根据机器人探索的预测区域与群内电池故障风险之间的帕累托折衷来衡量的。为了有效地平衡这两个相互矛盾的目标,采用了受生物启发的进化求解器,并在VREP仿真框架中实施的实际实验设置上进行了实践。获得的结果阐明了该方案的实用性,并提出了利用群中功率传输能力的未来研究。

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