Estimation of Physical Human-Robot Interaction Using Cost-Effective Pneumatic Padding

André Wilkening,Nikolina Puleva,Oleg Ivlev

doi:10.3390/robotics5030017

Abstract

The idea to use a cost-effective pneumatic padding for sensing of physical interaction between a user and wearable rehabilitation robots is not new, but until now there has not been any practical relevant realization. In this paper, we present a novel method to estimate physical human-robot interaction using a pneumatic padding based on artificial neural networks (ANNs). This estimation can serve as rough indicator of applied forces/torques by the user and can be applied for visual feedback about the user’s participation or as additional information for interaction controllers. Unlike common mostly very expensive 6-axis force/torque sensors (FTS), the proposed sensor system can be easily integrated in the design of physical human-robot interfaces of rehabilitation robots and adapts itself to the shape of the individual patient’s extremity by pressure changing in pneumatic chambers, in order to provide a safe physical interaction with high user’s comfort. This paper describes a concept of using ANNs for estimation of interaction forces/torques based on pressure variations of eight customized air-pad chambers. The ANNs were trained one-time offline using signals of a high precision FTS which is also used as reference sensor for experimental validation. Experiments with three different subjects confirm the functionality of the concept and the estimation algorithm.

Highlights

Robot-assisted therapy in neurorehabilitation after stroke or spinal cord injury is indicated to be an effective way of treatment [1,2,3], in order to support physiotherapists and due to this increase the treatment time for patients
The sensor system is based on eight air-pad chambers, that can be directly integrated in the cuff of human-robot interfaces, used to measure pressure distribution as well as to provide a safe physical human-robot interaction (HRI) with high user’s comfort
This paper presents a novel cost-effective sensor system using pneumatic padding that allows to estimate HRI forces/torques and provides high user’s comfort

Summary

Introduction

Robot-assisted therapy in neurorehabilitation after stroke or spinal cord injury is indicated to be an effective way of treatment [1,2,3], in order to support physiotherapists and due to this increase the treatment time for patients. In the design of those rehabilitation robots, an essential aspect is the physical human-robot interface, which should provide a safe human-robot interaction (HRI) with high comfort for the user Another critical point in the design is to include suitable force/torque sensors (FTS) to provide a measurement of interaction forces, that is used for development of interaction control strategies as well as information for visual feedback of amount of patient’s participation, which is useful to increase patient’s motivation. The sensor system is based on eight air-pad chambers, that can be directly integrated in the cuff of human-robot interfaces, used to measure pressure distribution as well as to provide a safe physical HRI with high user’s comfort. The estimation algorithm is tested with three subjects without retraining the ANNs to confirm functionality

Concept of Pneumatic Padding

Experimental Results

ANN Based Estimation

Conclusions