CAJ | 학술논문

为了解决多机器人在搜索过程中多任务分配和多机器人利用率问题，提出了一种带有即时拍卖的K-means聚类捆绑式拍卖算法。首先通过K-means聚类算法解决多机器人系统中的多任务捆绑问题，再运用捆绑式拍卖机制把聚类分配给相应的机器人。考虑各聚类内的任务完成情况和各机器人利用情况，相应机器人判断是否产生即时拍卖。仿真证明，该方法在多机器人搜索过程中节省资源且各机器人利用均衡。
위료해결다궤기인재수색과정중다임무분배화다궤기인이용솔문제，제출료일충대유즉시박매적K-means취류곤방식박매산법。수선통과K-means취류산법해결다궤기인계통중적다임무곤방문제，재운용곤방식박매궤제파취류분배급상응적궤기인。고필각취류내적임무완성정황화각궤기인이용정황，상응궤기인판단시부산생즉시박매。방진증명，해방법재다궤기인수색과정중절성자원차각궤기인이용균형。
In order to solve the problem of multi-robot in the search process of multi task allocation and multi-robot utilization, this paper presents a K-means clustering with instant auction algorithm based bundle auction.Firstly by using K-means clustering algorithm to solve the problem of multi tasks in multi robot binding ,then using bundled auction mechanism allocates the clusters to the corresponding robots. According to the completion of the tasks in each cluster ,the corresponding robot judge whether to make instant auction. Simulation results proves that this method of the multi-robot in the search process save resource and the robots use equilibrium.