用向量场统一控制机器人集群完成多种协同机动。
Versatile Distributed Maneuvering with Generalized Formations using Guiding Vector Fields
- 将机动分解为拦截与包围两独立虚拟坐标，构建无奇点的引导向量场。
- 支持编队跟踪、目标包围、环绕等多种复杂运动，无需重新设计控制器。
- 适合非完整约束机器人系统，理论与实验证明有效。
本文提出一种统一方法，实现广义编队下的多样化分布式机动。将机器人的运动分解为拦截与包围两个独立分量，分别由两个虚拟坐标参数化。将这两个虚拟坐标视为抽象流形的维度，推导出无奇点的引导向量场（GVF），结合基于一致性理论的分布式协调机制，使机器人能够实现多种运动，包括：(a) 编队跟踪，(b) 目标包围，(c) 环绕运动。可引入额外运动参数生成更复杂的协同动作。基于GVF设计了适用于非完整机器人模型的控制器。除理论分析外，通过大量仿真与实验验证了该方法的有效性。
原文摘要 · Abstract (English)
This paper presents a unified approach to realize versatile distributed maneuvering with generalized formations. Specifically, we decompose the robots' maneuvers into two independent components, i.e., interception and enclosing, which are parameterized by two independent virtual coordinates. Treating these two virtual coordinates as dimensions of an abstract manifold, we derive the corresponding singularity-free guiding vector field (GVF), which, along with a distributed coordination mechanism based on the consensus theory, guides robots to achieve various motions (i.e., versatile maneuvering), including (a) formation tracking, (b) target enclosing, and (c) circumnavigation. Additional motion parameters can generate more complex cooperative robot motions. Based on GVFs, we design a controller for a nonholonomic robot model. Besides the theoretical results, extensive simulations and experiments are performed to validate the effectiveness of the approach.
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