论文标题
使用分布式ADMM的轨迹计划，用于运动和感知不确定性的多机器人系统的连接维护
Connectivity Maintenance for Multi-Robot Systems Under Motion and Sensing Uncertainties Using Distributed ADMM-based Trajectory Planning
论文作者
论文摘要
机器人间通信使多机器人系统能够有效地协调和执行复杂任务。因此，对于许多多机器人系统，维持机器人之间的通信网络的连通性是必不可少的。在本文中，我们提出了一个轨迹计划者，用于维护多机器人系统。我们首先定义一个加权的无向图来表示系统的连接。与以前的连接维护作品不同，我们在制定图形边缘权重的同时明确说明机器人运动和感知不确定性。这些不确定性导致不确定的机器人位置直接影响系统的连通性。接下来，使用基于分布式交替的乘数（ADMM）框架的分布式交替方向方法，加权无向图的代数连接保持在指定下限上方。在这里，我们得出了ADMM优化步骤中所需的Hessian矩阵以减少计算负载所需的近似值。最后，提出了仿真结果，以从统计上验证我们的轨迹计划者的连通性维护。
Inter-robot communication enables multi-robot systems to coordinate and execute complex missions efficiently. Thus, maintaining connectivity of the communication network between robots is essential for many multi-robot systems. In this paper, we present a trajectory planner for connectivity maintenance of a multi-robot system. We first define a weighted undirected graph to represent the connectivity of the system. Unlike previous connectivity maintenance works, we explicitly account for robot motion and sensing uncertainties while formulating the graph edge weights. These uncertainties result in uncertain robot positions which directly affect the connectivity of the system. Next, the algebraic connectivity of the weighted undirected graph is maintained above a specified lower limit using a trajectory planner based on a distributed alternating direction method of multipliers (ADMM) framework. Here we derive an approximation for the Hessian matrices required within the ADMM optimization step to reduce the computational load. Finally, simulation results are presented to statistically validate the connectivity maintenance of our trajectory planner.
