arXiv:2609.07269cs.RO2026-09

提出无奇点的三维姿态路径跟踪向量场,可自由设计运动速度。

Singularity-Free Guiding Vector Fields on SO(3) with Designer-Specified Progression Behavior

  • 基于李群几何构造无奇点引导场,直接输出机体角速度控制输入。
  • 路径推进行为由用户指定函数控制,实现速度的精确设计。
  • 适用于需精确姿态控制的飞行器、机器人等平台,结构稳健可靠。

本文提出一种定义在特殊正交群 SO(3) 上的无奇点引导向量场(SF-GVF),用于姿态路径跟踪。通过将欧氏空间中的构造方法提升至 SO(3),结合增广状态与李群内在几何,得到闭式几何导引律,其积分曲线收敛至用户指定的姿态路径。该场定义于 SO(3) 的稠密开子集上,仅排除测度为零的对跖集合——这是 SO(3) 上连续全局稳定化的拓扑限制。该构造无需每步优化,且控制输入自然落在 so(3) 中,即机体角速率。进一步,将路径上的推进行为形式化为用户指定函数 ν(ξ),使参数化速度从隐含自由度变为首要设计变量。相较于欧氏情形中要求速度为零(v=0)的限制,SO(3) 中角速度为零(ω=0)对大多数具备主动姿态控制的平台是物理可行的,因而推进行为成为在 SO(3) 上可结构性利用的设计自由,而欧氏空间中不存在此特性。该框架在双不变黎曼度量下建立,对路径、推进行为及李雅普诺夫增益的选择具有统一有效性。仿真验证了在自交路径下恒定速度与点收敛推进行为的性能。

原文摘要 · Abstract (English)

This paper develops a singularity-free guiding vector field (SF-GVF) for path following on the special orthogonal group SO(3). First, we lift the Euclidean SF-GVF construction to SO(3), integrating the augmented-state approach with the intrinsic Lie-group geometry and obtaining a closed-form geometric guidance law whose integral curves converge to a designer-specified attitude path. The field is defined on a dense open subset of SO(3), excluding only the measure-zero antipodal set - a manifestation of the topological obstruction to continuous global stabilization on SO(3). The construction requires no per-step optimization and produces a control input intrinsically in so(3) as body angular rates. Second, we formalize the progression behavior along the path as a designer-supplied function \nu(\xi), promoting the parametric speed from an implicitly resolved degree of freedom to a first-class design specification. In contrast to the Euclidean condition v = 0, which excludes vehicles with minimum-speed constraints, the corresponding condition \omega = 0 on SO(3) is physically admissible for most platforms with active attitude control, making the progression behavior a design freedom structurally available on SO(3) but absent in the Euclidean setting. The framework's structural results are established under a bi-invariant Riemannian metric and hold uniformly across choices of path, progression, and Lyapunov gain. The framework is illustrated in simulation on self-intersecting paths under both constant and point-convergence progression behaviors.

姿态控制李群路径跟踪

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