Skip to main navigation Skip to search Skip to main content

PerKMP: Periodic Kernelized Movement Primitives for the Lower Limb Exoskeleton Real-Time Control and Transparency Enhancement

Haozhou Zeng, Yu Gu, Xiangzhi Liu, Min Pan, Tao Liu

Research output: Contribution to journalArticlepeer-review

6 Downloads (Pure)

Abstract

In the context of exoskeleton rehabilitation for patients in the later stages of recovery, reducing unnecessary interactive torque and enhancing exoskeleton transparency is important, where patients are encouraged to engage in voluntary movement. This study introduces a novel method known as Periodic Kernelized Movement Primitives (PerKMP) to address this issue. PerKMP is an advanced iteration of the original Kernelized Movement Primitives (KMP) that integrates periodic kernel functions for heightened adaptability. Two distinct PerKMP modules have been developed: the desired trajectory modulation PerKMP, which dynamically plans the desired trajectory according to the walking state, and the joint torque estimation PerKMP, which accurately estimates total joint torque in real-time and adjusts controller stiffness accordingly. A series of experiments with different walking speeds and different subjects were conducted to verify the validity of the method. Through the combined implementation of two PerKMP modules, the average absolute value of the interactive torque and energy per unit distance (EPUD) were reduced effectively. This research broadens the application of imitation learning methods in exoskeletons, and enables real-time control adjustments, thereby presenting a pioneering approach to enhancing the adaptability of exoskeleton rehabilitation systems. Note to Practitioners—Improving the performance of exoskeletons and reducing conflicts with humans during walking are crucial topics in the field of exoskeleton rehabilitation. This study presents a real-time method for reducing human-exoskeleton interactive torque, applicable to various walking speeds. The method adjusts the compliance controller’s desired trajectory and stiffness based on real-time encoder and torque sensor data, thereby reducing interactive torque. A series of experiments demonstrate that this method effectively reduces interactive torque across different speeds, enhancing the exoskeleton’s per...
Original languageEnglish
Pages (from-to)6448-6460
Number of pages13
JournalIEEE Transactions on Automation Science and Engineering
Volume23
Early online date11 Mar 2026
DOIs
Publication statusPublished - 11 Mar 2026

Funding

This work was supported in part by NSFC under Grant 52175033 and Grant U21A20120; and in part by the Key Research and Development Program of Zhejiang under Award 2023C03196, Award 2022C03103, and Award 2021C03051

Fingerprint

Dive into the research topics of 'PerKMP: Periodic Kernelized Movement Primitives for the Lower Limb Exoskeleton Real-Time Control and Transparency Enhancement'. Together they form a unique fingerprint.

Cite this