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Data Gathering Tours for Mobile Robots

机译:数据收集移动机器人的旅游

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摘要

We study a path planning problem which arises when multiple robots are used to gather data from stationary devices with wireless communication capabilities. Each device has a given communication range, and stores a fixed amount of data. The objective of the robots is to gather the data from these devices and to upload it to a base-station/gateway. We introduce a new optimization problem called the Data Gathering Problem (DGP). In DGP, the objective is to compute a tour for each robot in such a way that minimizes the time to collect data from all devices. In order to download the data from a device, a robot must visit a point within the communication range of the device. Then, it spends a fixed amount of time to download the data. Thus, the time to complete a tour depends on not only the travel time but also the time to download the data, and the number of devices visited along the tour. First, we study a special case of DGP where the robots' motion is restricted to a curve which contains the base station at one end. Next, we study the 2D version. We show that two existing algorithms for variants of the Traveling Salesperson Problem can be combined and adapted to obtain a constant factor approximation to DGP. Afterwards, we present an improvement for sparse deployments. We also present simulations which shed light on the utility of data gathering using mobile robots.
机译:我们研究了一条路径规划问题,当使用多个机器人来利用具有无线通信能力的固定设备的数据时出现。每个设备具有给定的通信范围,并存储固定量的数据。机器人的目的是收集来自这些设备的数据并将其上传到基站/网关。我们介绍了一种称为数据收集问题(DGP)的新优化问题。在DGP中,目标是以这样的方式计算每个机器人的游览,这使得能够最小化从所有设备收集数据的时间。为了从设备下载数据,机器人必须访问设备的通信范围内的点。然后,它花费了固定的时间来下载数据。因此,完成旅行的时间不仅取决于旅行时间,还取决于下载数据的时间,以及沿着旅游访问的设备数量。首先,我们研究一个特殊的DGP案例,其中机器人运动被限制在一个端一端包含基站的曲线。接下来,我们研究了2D版本。我们表明,可以组合两个用于旅行销售人员问题的变型的现有算法,并适于获得DGP的恒定因数近似。之后,我们提出了稀疏部署的改进。我们还展示了使用移动机器人收集的数据效用的模拟。

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