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Path Planning for a Connectivity Seeking Robot

机译:寻求连接性的机器人的路径规划

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We consider the scenario where an unmanned vehicle needs to get connected to a remote station (or another robot). More specifically, we consider the case where an unmanned vehicle is not connected in its current location and needs to incur motion energy to find a connected spot. We are then interested in designing robot paths that are energy efficient (minimum traveled distance) and can result in guaranteed connectivity in realistic channel environments that can experience multipath, shadowing, and path loss. In this paper, we show how this problem can be optimally and efficiently solved, under mild conditions on the paths, using tools from stochastic dynamic programming. Our extensive simulations, with real channel parameters, then confirm that our approach can significantly reduce the traveled distance to connectivity, thus minimizing the total energy consumption.
机译:我们考虑了无人驾驶汽车需要连接到远程站(或另一个机器人)的情况。更具体地说,我们考虑无人驾驶车辆在其当前位置未连接并且需要产生运动能量以找到连接点的情况。然后,我们对设计节能的机器人路径(最小的行进距离)感兴趣,并且可以在可能遇到多路径,阴影和路径损耗的真实通道环境中确保有保证的连接性。在本文中,我们展示了如何使用随机动态规划工具在路径温和的条件下最佳,有效地解决此问题。我们使用真实的信道参数进行了广泛的仿真,然后证实了我们的方法可以显着减少连接的行进距离,从而将总能耗降至最低。

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