Combining Movement Primitives with Contraction Theory

TL;DR

This paper introduces a modular motion planning framework that combines movement primitives with Contraction Theory, allowing flexible, stable, and independently modulated robot movements for complex tasks.

Contribution

It extends existing methods by enabling parallel and sequential combinations of discrete and rhythmic movements using Contraction Theory.

Findings

Framework demonstrates flexible movement combinations

Simulation shows improved motion planning versatility

Independent modulation of movements is achieved

Abstract

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.