Employing Laban Shape for Generating Emotionally and Functionally Expressive Trajectories in Robotic Manipulators

Fuente: arXiv
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Main Authors: Raghu, Srikrishna Bangalore, Lohrmann, Clare, Bakshi, Akshay, Kim, Jennifer, Herrera, Jose Caraveo, Hayes, Bradley, Roncone, Alessandro
Format: Preprint
Published: 2025
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author Raghu, Srikrishna Bangalore
Lohrmann, Clare
Bakshi, Akshay
Kim, Jennifer
Herrera, Jose Caraveo
Hayes, Bradley
Roncone, Alessandro
author_facet Raghu, Srikrishna Bangalore
Lohrmann, Clare
Bakshi, Akshay
Kim, Jennifer
Herrera, Jose Caraveo
Hayes, Bradley
Roncone, Alessandro
contents Successful human-robot collaboration depends on cohesive communication and a precise understanding of the robot's abilities, goals, and constraints. While robotic manipulators offer high precision, versatility, and productivity, they exhibit expressionless and monotonous motions that conceal the robot's intention, resulting in a lack of efficiency and transparency with humans. In this work, we use Laban notation, a dance annotation language, to enable robotic manipulators to generate trajectories with functional expressivity, where the robot uses nonverbal cues to communicate its abilities and the likelihood of succeeding at its task. We achieve this by introducing two novel variants of Hesitant expressive motion (Spoke-Like and Arc-Like). We also enhance the emotional expressivity of four existing emotive trajectories (Happy, Sad, Shy, and Angry) by augmenting Laban Effort usage with Laban Shape. The functionally expressive motions are validated via a human-subjects study, where participants equate both variants of Hesitant motion with reduced robot competency. The enhanced emotive trajectories are shown to be viewed as distinct emotions using the Valence-Arousal-Dominance (VAD) spectrum, corroborating the usage of Laban Shape.
format Preprint
id arxiv_https___arxiv_org_abs_2505_11716
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Employing Laban Shape for Generating Emotionally and Functionally Expressive Trajectories in Robotic Manipulators
Raghu, Srikrishna Bangalore
Lohrmann, Clare
Bakshi, Akshay
Kim, Jennifer
Herrera, Jose Caraveo
Hayes, Bradley
Roncone, Alessandro
Robotics
Successful human-robot collaboration depends on cohesive communication and a precise understanding of the robot's abilities, goals, and constraints. While robotic manipulators offer high precision, versatility, and productivity, they exhibit expressionless and monotonous motions that conceal the robot's intention, resulting in a lack of efficiency and transparency with humans. In this work, we use Laban notation, a dance annotation language, to enable robotic manipulators to generate trajectories with functional expressivity, where the robot uses nonverbal cues to communicate its abilities and the likelihood of succeeding at its task. We achieve this by introducing two novel variants of Hesitant expressive motion (Spoke-Like and Arc-Like). We also enhance the emotional expressivity of four existing emotive trajectories (Happy, Sad, Shy, and Angry) by augmenting Laban Effort usage with Laban Shape. The functionally expressive motions are validated via a human-subjects study, where participants equate both variants of Hesitant motion with reduced robot competency. The enhanced emotive trajectories are shown to be viewed as distinct emotions using the Valence-Arousal-Dominance (VAD) spectrum, corroborating the usage of Laban Shape.
title Employing Laban Shape for Generating Emotionally and Functionally Expressive Trajectories in Robotic Manipulators
topic Robotics
url https://arxiv.org/abs/2505.11716