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A Personalizable Controller for the Walking Assistive omNi-Directional Exo-Robot (WANDER)

A. Fortuna, M. Lorenzini, M. Leonori, JM. Gandarias, P. Balatti, Y. Cho, E. De Momi, A. Ajoudani

TL;DR

This work presents WANDER, an omnidirectional walking assistive exo-robot with a pelvic force/torque interface and a direction-based variable admittance controller. To tailor support to individual users, it introduces Preference-Based Optimization using the GLISp framework with an inverse distance weighting expansion and PSO-based acquisition to select subject-specific admittance parameters $M_{x,y}$ and $D_{x,y}$, validated on twelve participants. Results show significant reductions in linear energy $E_L$, angular energy $E_A$, and workload as measured by NASA-TLX, indicating improved comfort and mobility over fixed baselines, with notable inter-subject variability in optimal parameters. The findings support the feasibility of home- or clinic-based personalized gait assistance and point to future enhancements including anticipatory direction prediction and additional sensing for gait anomaly detection and fall prevention.

Abstract

Preserving and encouraging mobility in the elderly and adults with chronic conditions is of paramount importance. However, existing walking aids are either inadequate to provide sufficient support to users' stability or too bulky and poorly maneuverable to be used outside hospital environments. In addition, they all lack adaptability to individual requirements. To address these challenges, this paper introduces WANDER, a novel Walking Assistive omNi-Directional Exo-Robot. It consists of an omnidirectional platform and a robust aluminum structure mounted on top of it, which provides partial body weight support. A comfortable and minimally restrictive coupling interface embedded with a force/torque sensor allows to detect users' intentions, which are translated into command velocities by means of a variable admittance controller. An optimization technique based on users' preferences, i.e., Preference-Based Optimization (PBO) guides the choice of the admittance parameters (i.e., virtual mass and damping) to better fit subject-specific needs and characteristics. Experiments with twelve healthy subjects exhibited a significant decrease in energy consumption and jerk when using WANDER with PBO parameters as well as improved user performance and comfort. The great interpersonal variability in the optimized parameters highlights the importance of personalized control settings when walking with an assistive device, aiming to enhance users' comfort and mobility while ensuring reliable physical support.

A Personalizable Controller for the Walking Assistive omNi-Directional Exo-Robot (WANDER)

TL;DR

This work presents WANDER, an omnidirectional walking assistive exo-robot with a pelvic force/torque interface and a direction-based variable admittance controller. To tailor support to individual users, it introduces Preference-Based Optimization using the GLISp framework with an inverse distance weighting expansion and PSO-based acquisition to select subject-specific admittance parameters and , validated on twelve participants. Results show significant reductions in linear energy , angular energy , and workload as measured by NASA-TLX, indicating improved comfort and mobility over fixed baselines, with notable inter-subject variability in optimal parameters. The findings support the feasibility of home- or clinic-based personalized gait assistance and point to future enhancements including anticipatory direction prediction and additional sensing for gait anomaly detection and fall prevention.

Abstract

Preserving and encouraging mobility in the elderly and adults with chronic conditions is of paramount importance. However, existing walking aids are either inadequate to provide sufficient support to users' stability or too bulky and poorly maneuverable to be used outside hospital environments. In addition, they all lack adaptability to individual requirements. To address these challenges, this paper introduces WANDER, a novel Walking Assistive omNi-Directional Exo-Robot. It consists of an omnidirectional platform and a robust aluminum structure mounted on top of it, which provides partial body weight support. A comfortable and minimally restrictive coupling interface embedded with a force/torque sensor allows to detect users' intentions, which are translated into command velocities by means of a variable admittance controller. An optimization technique based on users' preferences, i.e., Preference-Based Optimization (PBO) guides the choice of the admittance parameters (i.e., virtual mass and damping) to better fit subject-specific needs and characteristics. Experiments with twelve healthy subjects exhibited a significant decrease in energy consumption and jerk when using WANDER with PBO parameters as well as improved user performance and comfort. The great interpersonal variability in the optimized parameters highlights the importance of personalized control settings when walking with an assistive device, aiming to enhance users' comfort and mobility while ensuring reliable physical support.
Paper Structure (21 sections, 18 equations, 4 figures, 2 tables)

This paper contains 21 sections, 18 equations, 4 figures, 2 tables.

Table of Contents

  1. INTRODUCTION
  2. Exo-robot for Walking Assistance
  3. Hardware Overview
  4. Control System
  5. Preference-based Optimization
  6. Surrogate function
  7. Inverse Distance Weighting function
  8. Acquisition function optimization
  9. Experiments
  10. Experimental protocol
  11. Optimization
  12. Evaluation
  13. Experimental analysis
  14. Quantitative metrics
  15. Qualitative metrics
  16. ...and 6 more sections

Figures (4)

  • Figure 1: Overview of WANDER and its control framework schema including the preference-based optimization (PBO) of the control parameters.
  • Figure 2: Path followed by the users during the evaluation phase.
  • Figure 3: Results of the linear energy, angular energy, and jerk, for all the subjects in the three experimental conditions (LT1, LT2, PBO). By using WANDER with PBO parameters, a jerk profile comparable to a very damped system and a lower energy profile comparable to a lightweight system can be obtained, providing the capabilities of the PBO method in finding optimal parameters. $*$ stands for $p<0.05$.
  • Figure 4: Results of the NASA-TLX for all the subjects in the three experimental conditions (LT1, LT2, PBO). The boxplots for mental demand (MD), physical demand (PD), temporal demand (TD), performance (P), effort (E), and frustration (F) are presented. $*$ stands for $p<0.05$.