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Coalition Formation Games for Dynamic Multirobot Tasks

机译:用于动态多机器人任务的联盟形成游戏

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This paper studies the problem of forming coalitions for dynamic tasks in multirobot systems. As robots - either individually or in groups - encounter new tasks for which individual or group resources do not suffice, robot coalitions that are collectively capable of meeting these requirements need to be formed. We propose an approach where such tasks are reported to a task coordinator that is responsible for coalition formation. The novelty of this approach is that the process of determining these coalitions is modeled as a coalition formation game where groups of robots are evaluated with respect to resources and cost. As such, the resulting coalitions are ensured so that no group of robots has a viable alternative to staying within their assigned coalition. The newly determined coalitions are then conveyed to the robots which then form the coalitions as instructed. As new tasks are encountered, coalitions merge and split so that the resulting coalitions are capable of doing the newly encountered tasks. Extensive simulations demonstrate the effectiveness of the proposed approach in a wide range of tasks.
机译:本文研究形成对多机器人系统的动态任务,联盟的问题。由于机器人 - 无论是个人或团体 - 为其个人或团体的资源不足遭遇新的任务,机器人联盟是集体能够满足这些要求的需要形成。我们提出这些任务的报告给任务协调员,负责联盟形成的方法。这种方法的新颖性在于,确定这些联盟的过程被建模为联盟形成游戏,其中机器人的基团相对于资源和成本进行评估。因此,所产生的联盟都保证让没有组机器人有一个可行的替代方案分配给他们的联盟内停留。然后,将新确定的联盟被输送到机器人然后形成联盟的指示。当遇到新的任务,联盟合并和拆分使得所得到的联盟能够做新遇到的任务。大量的模拟展示多种任务的提出方法的有效性。

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