用收缩理论整合动作基元，让机器人灵活组合复杂运动。
Combining Movement Primitives with Contraction Theory
- 基于收缩理论构建模块化运动规划框架
- 支持离散与周期性动作的串并联组合
- 适合需要灵活编排复杂动作的机器人研究
本文提出一种基于动作基元的运动规划模块化框架。核心是收缩理论——一种用于非线性动力系统模块化稳定性的工具。该方法扩展了以往工作，实现了离散与周期性动作的并行和串行组合，同时支持对每个动作的独立调节。这一模块化框架使得复杂机器人运动规划可采用分而治之策略，简化编程。仿真结果展示了该框架的灵活性与通用性，凸显其在应对多样机器人运动规划挑战中的潜力。
原文摘要 · Abstract (English)
This paper presents a modular framework for motion planning using movement primitives. Central to the approach is Contraction Theory, a modular stability tool for nonlinear dynamical systems. The approach extends prior methods by achieving parallel and sequential combinations of both discrete and rhythmic movements, while enabling independent modulation of each movement. This modular framework enables a divide-and-conquer strategy to simplify the programming of complex robot motion planning. Simulation examples illustrate the flexibility and versatility of the framework, highlighting its potential to address diverse challenges in robot motion planning.
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