论文标题

基于分布式估计的自组织多边形形成控制

Self-organized Polygon Formation Control based on Distributed Estimation

论文作者

Yang, Qingkai, Xiao, Fan, Lyu, Jingshuo, Zhou, Bo, Fang, Hao

论文摘要

本文研究了控制多机器人系统以自组织方式实现多边形形成的问题。不同的是,与典型的形态控制策略进行了转向机器人以满足预定义的控制变量,例如成对距离,相对位置和轴承,本文最重要的想法是通过将控制输入随机注入多边形的形态,以使几个机器人(例如,沿着该组的近距离构图)的近距离构图(例如,沿着二点)的近距离构图(例如,pertex机器人)。在我们的问题中,机器人最初分布在飞机上。 Sopalled Vertex机器人负责确定整个编队的几何形状及其整体大小,而其他人则移动,以最大程度地减少两个直接邻居的差异。在第一步中,每个顶点机器人估计其相关链中机器人的数量。用于估计的两种类型的控制输入是使用最新和最后两次瞬间的测量设计设计的。在第二步中,提出了自组织的形成控制法,只有顶点机器人收到外部信息。两种估计策略之间的比较是根据收敛速度和稳健性进行的。在模拟和物理实验中,整个控制框架的有效性得到了进一步验证。

This paper studies the problem of controlling a multi-robot system to achieve a polygon formation in a self-organized manner. Different from the typical formation control strategies where robots are steered to satisfy the predefined control variables, such as pairwise distances, relative positions and bearings, the foremost idea of this paper is to achieve polygon formations by injecting control inputs randomly to a few robots (say, vertex robots) of the group, and the rest follow the simple principles of moving towards the midpoint of their two nearest neighbors in the ring graph without any external inputs. In our problem, a fleet of robots is initially distributed in the plane. The socalled vertex robots take the responsibility of determining the geometric shape of the entire formation and its overall size, while the others move so as to minimize the differences with two direct neighbors. In the first step, each vertex robot estimates the number of robots in its associated chain. Two types of control inputs that serve for the estimation are designed using the measurements from the latest and the last two time instants respectively. In the second step, the self-organized formation control law is proposed where only vertex robots receive external information. Comparisons between the two estimation strategies are carried out in terms of the convergence speed and robustness. The effectiveness of the whole control framework is further validated in both simulation and physical experiments.

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