The hardware domain adopts a distributed control architecture in which functions are divided across multiple specialized modules. Each module provides a clearly defined role within the robotic system.

Sim-to-real Actuator Modules (SAM)
Mechanical actuation units equipped with backdrivable and low-impedance joint mechanisms.
These modules generate the physical interaction forces required for assistance and are designed for high responsiveness and transparency.

Motor Drivers (MD)

Embedded motor-control units that handle real-time current control, sensor acquisition, and hardware-level protection.
MDs form the lowest layer of the control hierarchy and ensure stable torque generation with deterministic timing.

Control Modules (CM)

Mid-level controllers responsible for executing validated control algorithms, managing the distributed system, synchronizing modules, and supervising safety-critical behaviors. CMs maintain the core operational logic of the wearable robot.

Application Modules (AM)

High-level coordination units that implement task-specific robot functions.
AMs interpret system states, manage multi-joint behaviors, and configure robot operation according to the intended application scenario.

Extension Modules (XM)

Flexible development modules that support rapid prototyping, sensor integration, external device interfacing, and algorithm testing.
XMs enable researchers to deploy and evaluate new control strategies without modifying safety-critical components.

Apparel Modules

Human-interfacing components including waist interfaces, back-support frames, and other adjustable structures.
These modules are designed with a modular fitting mechanism to accommodate diverse body shapes and ensure stable, comfortable attachment.

The software domain provides a standardized control framework and a data-centric computing environment that supports real-time operation and AI-enhanced analysis.

Unified Control and Communication Structure

A standardized FSM-based control architecture specifies operational states, transition logic, and reference generation across modules.
A CAN-based communication protocol enables high-speed and robust data exchange within the distributed control architecture.
Integrated real-time monitoring tools provide visibility into system variables, supporting debugging, parameter tuning, and clinical evaluation.

Data and AI Infrastructure

A unified data pipeline supports large-scale logging, structured dataset formatting, cloud connectivity, and AI-based model training.
This framework enables data-driven personalization, performance optimization, and long-term analysis of human–robot interaction.

Platform Vision

By combining a distributed hardware architecture with a unified software ecosystem, the Wearable Robot Platform enables rapid development, cross-system compatibility, and data-driven optimization. This platform supports the laboratory’s research in assistive, rehabilitative, and industrial wearable robotics while providing a scalable foundation for future expansion.