Dynamic Movement Primitives in Robotics: A Tutorial Survey

TL;DR

This tutorial survey comprehensively reviews Dynamic Movement Primitives (DMPs) in robotics, covering mathematical formulations, practical implementations, and research trends, highlighting their role in generating adaptable motor commands inspired by biological systems.

Contribution

It provides a systematic review of DMP formulations, discusses their advantages and limitations, and offers practical implementation insights and future research directions.

Findings

Multiple DMP formulations with distinct advantages and limitations

Practical implementations and released code for DMP approaches

Identification of research gaps and future directions in DMP development

Abstract

Biological systems, including human beings, have the innate ability to perform complex tasks in versatile and agile manner. Researchers in sensorimotor control have tried to understand and formally define this innate property. The idea, supported by several experimental findings, that biological systems are able to combine and adapt basic units of motion into complex tasks finally lead to the formulation of the motor primitives theory. In this respect, Dynamic Movement Primitives (DMPs) represent an elegant mathematical formulation of the motor primitives as stable dynamical systems, and are well suited to generate motor commands for artificial systems like robots. In the last decades, DMPs have inspired researchers in different robotic fields including imitation and reinforcement learning, optimal control,physical interaction, and human-robot co-working, resulting a considerable amount of published papers. The goal of this tutorial survey is two-fold. On one side, we present the existing DMPs formulations in rigorous mathematical terms,and discuss advantages and limitations of each approach as well as practical implementation details. In the tutorial vein, we also search for existing implementations of presented approaches and release several others. On the other side, we provide a systematic and comprehensive review of existing literature and categorize state of the art work on DMP. The paper concludes with a discussion on the limitations of DMPs and an outline of possible research directions.