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

Yifan Wang, Sherwin Stephen Chan, Mingyuan Lei, Lek Syn Lim, Henry Johan, Bingran Zuo, Wei Tech Ang

TL;DR

This work introduces a HITL simulation framework tailored for gait assistive robots to address the unique challenges of passive support systems. By building human and robot digital twins and a six-DoF pHRI interaction model, it enables quantitative, cross-environment evaluation of control strategies, including a speed-adaptive controller versus a PID baseline. The study demonstrates that the speed-adaptive controller improves compliance and reduces gait distortion, while revealing notable differences between real and simulated adaptation that affect locomotion dynamics. Overall, the framework offers a versatile tool for developing personalized control policies for diverse users in safe, controlled settings.

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.

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

TL;DR

This work introduces a HITL simulation framework tailored for gait assistive robots to address the unique challenges of passive support systems. By building human and robot digital twins and a six-DoF pHRI interaction model, it enables quantitative, cross-environment evaluation of control strategies, including a speed-adaptive controller versus a PID baseline. The study demonstrates that the speed-adaptive controller improves compliance and reduces gait distortion, while revealing notable differences between real and simulated adaptation that affect locomotion dynamics. Overall, the framework offers a versatile tool for developing personalized control policies for diverse users in safe, controlled settings.

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.

Paper Structure

This paper contains 16 sections, 1 equation, 3 figures, 3 tables.

Table of Contents

  1. INTRODUCTION
  2. HUMAN-IN-THE-LOOP SIMULATION FRAMEWORK
  3. Human Digital Twin
  4. Robot Digital Twin
  5. Physical Human-Robot Interaction Model
  6. HUMAN-ROBOT INTERACTION EVALUATION
  7. Experiment Protocol
  8. Data Processing and Evaluation Metrics
  9. Real and Sim Validation
  10. Controller Performance Evaluation
  11. RESULTS AND DISCUSSION
  12. Real and Sim Validation
  13. Range of Motion Differences
  14. Physical Human-Robot Interaction Differences
  15. Controller Performance
  16. ...and 1 more sections

Figures (3)

  • Figure 1: Overview of the Human-in-the-Loop (HITL) simulation framework for gait assistive robots. (a) Human digital twin: The process includes using body anthropometry to generate a personalized skeleton model. This model has a walking control policy with varied balance abilities based on the reference motion to create a human digital twin. (b) MRBA digital twin: A CAD model, combined with real system dynamics and control architecture, is used to develop the MRBA digital twin. (c) Physical Human-Robot Interaction (pHRI) model: The human digital twin is constrained with a six-DoF mass-spring-damper mechanism representing the robotic arm with a soft harness.
  • Figure 2: Statistical Parametric Mapping (SPM1D) one-dimensional analysis comparing the motion patterns of the subject in simulation and real-world settings.
  • Figure 3: Comparison of lower limb joint kinematics for (a) real-world and (b) simulation. The graphs show the joint angles in the sagittal plane for the pelvis, hip, knee, and ankle joints over a complete gait cycle. FW indicates free walking without the robot, PID denotes the use of the PID controller for the follow-me function of MRBA, and Adaptive denotes the speed-adaptive controller for the follow-me function of MRBA. The shaded areas represent the standard deviation of the joint angles across multiple gait cycles.