A Hierarchical Distributed Control System Design for Lower Limb Rehabilitation Robot

With the acceleration of global aging and the rising incidence of stroke, the demand for lower limb rehabilitation has been steadily increasing. Traditional therapeutic methods can no longer meet the growing needs, which has led to the widespread application of robotic solutions to address labor shortages. In this context, this paper presents a hierarchical and distributed control system based on ROS 2 and Micro-ROS. The distributed architecture decouples functional modules, improving system maintainability and supporting modular upgrades. The control system consists of a three-layer structure, including a high-level controller, Jetson Nano, for gait data processing and advanced command generation; a middle-layer controller, ESP32-S3, for sensor data fusion and inter-layer communication bridging; and a low-level controller, STM32F405, for field-oriented control to drive the motors along a predefined trajectory. Experimental validation in both early and late rehabilitation stages demonstrates the system’s ability to achieve accurate trajectory tracking. In the early rehabilitation stage, the maximum root mean square error of the joint motors is 1.143°; in the later rehabilitation stage, the maximum root mean square error of the joint motors is 1.833°, confirming the robustness of the control system. Additionally, the hierarchical and distributed architecture ensures maintainability and facilitates future upgrades. This paper provides a feasible control scheme for the next generation of lower limb rehabilitation robots.

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Publication Details

Journal
Technologies
Published
2025-10-13
DOI
https://doi.org/10.3390/technologies13100462
Citations
1
Primary Topic
Prosthetics and Rehabilitation Robotics
Type
article
Field-Weighted Citation Impact
0.67
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A Hierarchical Distributed Control System Design for Lower Limb Rehabilitation Robot

Aihui Wang, Xiang Zhang, Xuebin Yue, Ping Liu et al.
1 citations
Technologies
Prosthetics and Rehabilitation Robotics
0.67
article

A Hierarchical Distributed Control System Design for Lower Limb Rehabilitation Robot

Aihui Wang, Xiang Zhang, Xuebin Yue, Ping Liu, Rui Teng, Juwei Dong
article en
1 citations

Abstract

With the acceleration of global aging and the rising incidence of stroke, the demand for lower limb rehabilitation has been steadily increasing. Traditional therapeutic methods can no longer meet the growing needs, which has led to the widespread application of robotic solutions to address labor shortages. In this context, this paper presents a hierarchical and distributed control system based on ROS 2 and Micro-ROS. The distributed architecture decouples functional modules, improving system maintainability and supporting modular upgrades. The control system consists of a three-layer structure, including a high-level controller, Jetson Nano, for gait data processing and advanced command generation; a middle-layer controller, ESP32-S3, for sensor data fusion and inter-layer communication bridging; and a low-level controller, STM32F405, for field-oriented control to drive the motors along a predefined trajectory. Experimental validation in both early and late rehabilitation stages demonstrates the system’s ability to achieve accurate trajectory tracking. In the early rehabilitation stage, the maximum root mean square error of the joint motors is 1.143°; in the later rehabilitation stage, the maximum root mean square error of the joint motors is 1.833°, confirming the robustness of the control system. Additionally, the hierarchical and distributed architecture ensures maintainability and facilitates future upgrades. This paper provides a feasible control scheme for the next generation of lower limb rehabilitation robots.

TechnologiesVol. 13(10)
Zhongyuan University of Technology (CN)
Openalex Percentile: Top 26%
Prosthetics and Rehabilitation Robotics
0.67
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A Hierarchical Distributed Control System Design for Lower Limb Rehabilitation Robot — Aihui Wang, Xiang Zhang, et al. · Technologies (2025) | TGRS Research Map | TGRS