This paper considers trajectory planning for a mobile robot which persistently relays data between pairs of far-away communication nodes. Data accumulates stochastically at each source, and the robot must move to appropriate positions to enable data offload to the corresponding destination. The robot needs to minimize the average time that data waits at a source before being serviced. We are interested in finding optimal robotic routing policies consisting of 1) locations where the robot stops to relay (relay positions) and 2) conditional transition probabilities that determine the sequence in which the pairs are serviced. We first pose this problem as a non-convex problem that optimizes over both relay positions and transition probabilities. To find approximate solutions, we propose a novel algorithm which alternately optimizes relay positions and transition probabilities. For the former, we find efficient convex partitions of the non-convex relay regions, then formulate a mixed-integer second-order cone problem. For the latter, we find optimal transition probabilities via sequential least squares programming. We extensively analyze the proposed approach and mathematically characterize important system properties related to the robot's long-term energy consumption and service rate. Finally, through extensive simulation with real channel parameters, we verify the efficacy of our approach.
翻译:本文探讨移动机器人的轨迹规划,该机器人在远方通信节点之间持续转发数据。 数据在每个源头累积, 并且机器人必须移动到合适的位置, 以便能够将数据卸载到相应的目的地。 机器人需要尽可能缩短数据在源头等待的平均时间。 我们感兴趣的是找到最佳的机器人路由政策, 包括:(1) 机器人停止中继( 后置位置) 和(2) 有条件的过渡概率, 从而决定对配对服务的顺序。 我们首先将这一问题作为一个非 convex 问题提出来, 因为它能优化中继位置和过渡概率。 为了找到近似的解决办法, 我们建议一种新的算法, 以其他方式优化中继位置和过渡概率。 对于前者, 我们能找到非convex 中继区域高效的 convex 分区, 然后形成一个混合的二阶调调调调调调调调问题。 对于后者, 我们通过按顺序最小平方程式来找到最佳的过渡概率。 我们广泛分析拟议的方法, 并且从数学角度分析与我们长期消费率相关的真实系统特性, 校准我们通过机器人系统测算法 。