Hands-On Robotics: Enabling Communication Through Direct Gesture Control

Fuente: arXiv
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Autori principali: Pascher, Max, Saad, Alia, Liebers, Jonathan, Heger, Roman, Gerken, Jens, Schneegass, Stefan, Gruene, Uwe
Natura: Preprint
Pubblicazione: 2024
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author Pascher, Max
Saad, Alia
Liebers, Jonathan
Heger, Roman
Gerken, Jens
Schneegass, Stefan
Gruene, Uwe
author_facet Pascher, Max
Saad, Alia
Liebers, Jonathan
Heger, Roman
Gerken, Jens
Schneegass, Stefan
Gruene, Uwe
contents Effective Human-Robot Interaction (HRI) is fundamental to seamlessly integrating robotic systems into our daily lives. However, current communication modes require additional technological interfaces, which can be cumbersome and indirect. This paper presents a novel approach, using direct motion-based communication by moving a robot's end effector. Our strategy enables users to communicate with a robot by using four distinct gestures -- two handshakes ('formal' and 'informal') and two letters ('W' and 'S'). As a proof-of-concept, we conducted a user study with 16 participants, capturing subjective experience ratings and objective data for training machine learning classifiers. Our findings show that the four different gestures performed by moving the robot's end effector can be distinguished with close to 100% accuracy. Our research offers implications for the design of future HRI interfaces, suggesting that motion-based interaction can empower human operators to communicate directly with robots, removing the necessity for additional hardware.
format Preprint
id arxiv_https___arxiv_org_abs_2401_09077
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Hands-On Robotics: Enabling Communication Through Direct Gesture Control
Pascher, Max
Saad, Alia
Liebers, Jonathan
Heger, Roman
Gerken, Jens
Schneegass, Stefan
Gruene, Uwe
Human-Computer Interaction
Robotics
Effective Human-Robot Interaction (HRI) is fundamental to seamlessly integrating robotic systems into our daily lives. However, current communication modes require additional technological interfaces, which can be cumbersome and indirect. This paper presents a novel approach, using direct motion-based communication by moving a robot's end effector. Our strategy enables users to communicate with a robot by using four distinct gestures -- two handshakes ('formal' and 'informal') and two letters ('W' and 'S'). As a proof-of-concept, we conducted a user study with 16 participants, capturing subjective experience ratings and objective data for training machine learning classifiers. Our findings show that the four different gestures performed by moving the robot's end effector can be distinguished with close to 100% accuracy. Our research offers implications for the design of future HRI interfaces, suggesting that motion-based interaction can empower human operators to communicate directly with robots, removing the necessity for additional hardware.
title Hands-On Robotics: Enabling Communication Through Direct Gesture Control
topic Human-Computer Interaction
Robotics
url https://arxiv.org/abs/2401.09077