A Multi-Modal Feedback Communication Interface for Human Working Posture Adjustments

Conference paper (2023)

Authors

Kushal Thirani Student
David Abbink Human-Robot Interaction - Mechanical, Maritime and Materials Engineering
L. Peternel Human-Robot Interaction - Mechanical, Maritime and Materials Engineering
Research Group
Human-Robot Interaction (Mechanical, Maritime and Materials Engineering) (TU Delft)
Copyright: © 2023 Kushal Thirani, D.A. Abbink, L. Peternel
DOI: https://doi.org/10.1007/978-3-031-22731-8_2
Ergonomics Human factors Human-machine interaction Visual feedback Audio feedback
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Published Date

2023

Language

English

Reuse Rights

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Faculty

Mechanical, Maritime and Materials Engineering

Department

Cognitive Robotics

Research Group

Human-Robot Interaction

Abstract

This paper studies non-physical feedback mechanisms to guide human workers toward ergonomic body postures. Specifically, the focus is to solve the tasks that involve no direct physical interaction between the human and the robotic system, therefore tactile guidance by the robot body is not feasible. We propose a multi-modal ergonomic posture guidance system that comprises visual feedback and speech-based audio feedback. We hypothesise that the proposed multi-modal system leads to better performance compared to uni-modal feedback systems when trying to guide users from one pose to another. To test the hypothesis we conducted an experiment that compared conditions with only audio feedback, only visual feedback and multi-modal feedback. In addition, we examined speech-based audio guidance in joint space and in endpoint space. The results showed that the speech-based feedback in joint space came out as the preferred audio feedback due to its ability to allow users to carry out efficient and coordinated inter-joint movements, especially in cases of high redundancy. Furthermore, the proposed multi-modal feedback system was superior compared to the other feedback modalities both in terms of objective measures and subjective measures.