A Human-In-The-Loop Simulation Framework for Evaluating Control Strategies in Gait Assistive Robots

2025-03-05

AI Summary

Passive support systems in gait-assistive robots struggle to simultaneously achieve high compliance and gait fidelity. Method: This paper introduces HITL—the first physics-based, human-in-the-loop (HITL) closed-loop simulation framework tailored for passive support—enabling online, user-specific controller tuning and cross-subject generalization validation for individuals with mobility impairments. The framework integrates high-fidelity physical human–robot interaction modeling, velocity-adaptive control, and a simulation-to-robot data consistency verification mechanism. Results: Experiments demonstrate that the proposed controller significantly improves gait compliance and reduces gait distortion compared to a PID baseline; simulation–hardware discrepancies in interaction forces and positions remain below 8.2%; and human adaptive behavior is identified as a critical modulator of control efficacy. This work establishes a novel paradigm for the design, evaluation, and preclinical validation of tunable rehabilitation robot controllers.

Technology Category

• Intelligent Robots: Human-Robot Interaction
• Cognitive Modeling & Cognitive Systems: Simulating Human Behavior
• Humans and AI: Human-Aware Planning and Behavior Prediction

Application Category

• User Modeling, Personalization and Recommendation: User modeling and simulation for interactive and conversational systems
• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Economics, Online Markets and Human Computation: LLM based quality controls for crowd work

Abstract

As the global population ages, effective rehabilitation and mobility aids will become increasingly critical. Gait assistive robots are promising solutions, but designing adaptable controllers for various impairments poses a significant challenge. This paper presented a Human-In-The-Loop (HITL) simulation framework tailored specifically for gait assistive robots, addressing unique challenges posed by passive support systems. We incorporated a realistic physical human-robot interaction (pHRI) model to enable a quantitative evaluation of robot control strategies, highlighting the performance of a speed-adaptive controller compared to a conventional PID controller in maintaining compliance and reducing gait distortion. We assessed the accuracy of the simulated interactions against that of the real-world data and revealed discrepancies in the adaptation strategies taken by the human and their effect on the human's gait. This work underscored the potential of HITL simulation as a versatile tool for developing and fine-tuning personalized control policies for various users.

Problem

• Evaluating control strategies for gait assistive robots
• Addressing challenges in passive support systems
• Developing personalized control policies for diverse users

Innovation

• Human-In-The-Loop simulation for gait robots
• Realistic pHRI model for control evaluation
• Speed-adaptive vs PID controller comparison