Toward Human-Robot Co-learning in Manufacturing

Emilia Pietras; Raquel Salcedo Gil; Guglielmo Borzone; Sonja Rispens; Leon Bodenhagen

doi:10.1007/978-981-95-2382-5_55

Toward Human-Robot Co-learning in Manufacturing

Emilia Pietras (Corresponding author)
, Raquel Salcedo Gil
, Guglielmo Borzone
, Sonja Rispens
, Leon Bodenhagen

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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Abstract

As robot systems are increasingly being implemented in manufacturing workspaces, effective employee training becomes essential. We propose an ontology-based guidance system which adapts its instructional guidance to the inferred expertise level of the operator. Through a pilot study with six participants we found that interactions with the guidance system changed visibly after the first session, implying changes in the need for guidance over time. Furthermore, robot-use self-efficacy increased significantly after interacting with the robot, indicating that the system supported both learning and confidence development.

Original language	English
Title of host publication	Social Robotics + AI
Subtitle of host publication	17th International Conference, ICSR+AI 2025, Naples, Italy, September 10–12, 2025, Proceedings
Editors	Mariacarla Staffa, John-John Cabibihan, Bruno Siciliano, Shuzhi Sam Ge, Leon Bodenhagen, Adriana Tapus, Silvia Rossi, Filippo Cavallo, Laura Fiorini, Marco Matarese, Hongsheng He
Place of Publication	Singapore
Publisher	Springer
Pages	650–657
Number of pages	8
Volume	II
ISBN (Electronic)	978-981-95-2382-5
ISBN (Print)	978-981-95-2381-8
DOIs	https://doi.org/10.1007/978-981-95-2382-5_55
Publication status	Published - 2 Jan 2026
Event	17th International Conference on Social Robotics + AI, ICSR + AI 2025 - Naples, Italy Duration: 10 Sept 2025 → 12 Sept 2025

Publication series

Name	Lecture Notes in Computer Science (LNCS)
Volume	16132
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Name	Lecture Notes in Artificial Intelligence (LNAI)
Volume	16132
ISSN (Print)	2945-9133
ISSN (Electronic)	2945-9141

Conference

Conference	17th International Conference on Social Robotics + AI, ICSR + AI 2025
Abbreviated title	ICSR + AI 2025
Country/Territory	Italy
City	Naples
Period	10/09/25 → 12/09/25

Funding

This work has been funded by the EU project Fluently (Grant agreement ID: 101058680) and by the Industry 4.0 lab at the University of Southern Denmark.

Keywords

Adaptation
Collaborative robotics
Learning

Access to Document

10.1007/978-981-95-2382-5_55

pdfFinal published version, 854 KBLicence: TAVERNE

Cite this

Pietras, E., Salcedo Gil, R., Borzone, G., Rispens, S., & Bodenhagen, L. (2026). Toward Human-Robot Co-learning in Manufacturing. In M. Staffa, J.-J. Cabibihan, B. Siciliano, S. S. Ge, L. Bodenhagen, A. Tapus, S. Rossi, F. Cavallo, L. Fiorini, M. Matarese, & H. He (Eds.), Social Robotics + AI: 17th International Conference, ICSR+AI 2025, Naples, Italy, September 10–12, 2025, Proceedings (Vol. II, pp. 650–657). (Lecture Notes in Computer Science (LNCS); Vol. 16132), (Lecture Notes in Artificial Intelligence (LNAI); Vol. 16132). Springer. https://doi.org/10.1007/978-981-95-2382-5_55

Pietras, Emilia ; Salcedo Gil, Raquel ; Borzone, Guglielmo et al. / Toward Human-Robot Co-learning in Manufacturing. Social Robotics + AI: 17th International Conference, ICSR+AI 2025, Naples, Italy, September 10–12, 2025, Proceedings. editor / Mariacarla Staffa ; John-John Cabibihan ; Bruno Siciliano ; Shuzhi Sam Ge ; Leon Bodenhagen ; Adriana Tapus ; Silvia Rossi ; Filippo Cavallo ; Laura Fiorini ; Marco Matarese ; Hongsheng He. Vol. II Singapore : Springer, 2026. pp. 650–657 (Lecture Notes in Computer Science (LNCS)). (Lecture Notes in Artificial Intelligence (LNAI)).

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title = "Toward Human-Robot Co-learning in Manufacturing",

abstract = "As robot systems are increasingly being implemented in manufacturing workspaces, effective employee training becomes essential. We propose an ontology-based guidance system which adapts its instructional guidance to the inferred expertise level of the operator. Through a pilot study with six participants we found that interactions with the guidance system changed visibly after the first session, implying changes in the need for guidance over time. Furthermore, robot-use self-efficacy increased significantly after interacting with the robot, indicating that the system supported both learning and confidence development.",

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booktitle = "Social Robotics + AI",

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Pietras, E, Salcedo Gil, R, Borzone, G, Rispens, S & Bodenhagen, L 2026, Toward Human-Robot Co-learning in Manufacturing. in M Staffa, J-J Cabibihan, B Siciliano, SS Ge, L Bodenhagen, A Tapus, S Rossi, F Cavallo, L Fiorini, M Matarese & H He (eds), Social Robotics + AI: 17th International Conference, ICSR+AI 2025, Naples, Italy, September 10–12, 2025, Proceedings. vol. II, Lecture Notes in Computer Science (LNCS), vol. 16132, Lecture Notes in Artificial Intelligence (LNAI), vol. 16132, Springer, Singapore, pp. 650–657, 17th International Conference on Social Robotics + AI, ICSR + AI 2025, Naples, Italy, 10/09/25. https://doi.org/10.1007/978-981-95-2382-5_55

Toward Human-Robot Co-learning in Manufacturing. / Pietras, Emilia (Corresponding author); Salcedo Gil, Raquel; Borzone, Guglielmo et al.
Social Robotics + AI: 17th International Conference, ICSR+AI 2025, Naples, Italy, September 10–12, 2025, Proceedings. ed. / Mariacarla Staffa; John-John Cabibihan; Bruno Siciliano; Shuzhi Sam Ge; Leon Bodenhagen; Adriana Tapus; Silvia Rossi; Filippo Cavallo; Laura Fiorini; Marco Matarese; Hongsheng He. Vol. II Singapore: Springer, 2026. p. 650–657 (Lecture Notes in Computer Science (LNCS); Vol. 16132), (Lecture Notes in Artificial Intelligence (LNAI); Vol. 16132).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

T1 - Toward Human-Robot Co-learning in Manufacturing

AU - Pietras, Emilia

AU - Salcedo Gil, Raquel

AU - Borzone, Guglielmo

AU - Rispens, Sonja

AU - Bodenhagen, Leon

PY - 2026/1/2

Y1 - 2026/1/2

N2 - As robot systems are increasingly being implemented in manufacturing workspaces, effective employee training becomes essential. We propose an ontology-based guidance system which adapts its instructional guidance to the inferred expertise level of the operator. Through a pilot study with six participants we found that interactions with the guidance system changed visibly after the first session, implying changes in the need for guidance over time. Furthermore, robot-use self-efficacy increased significantly after interacting with the robot, indicating that the system supported both learning and confidence development.

AB - As robot systems are increasingly being implemented in manufacturing workspaces, effective employee training becomes essential. We propose an ontology-based guidance system which adapts its instructional guidance to the inferred expertise level of the operator. Through a pilot study with six participants we found that interactions with the guidance system changed visibly after the first session, implying changes in the need for guidance over time. Furthermore, robot-use self-efficacy increased significantly after interacting with the robot, indicating that the system supported both learning and confidence development.

KW - Adaptation

KW - Collaborative robotics

KW - Learning

UR - https://www.scopus.com/pages/publications/105032755470

U2 - 10.1007/978-981-95-2382-5_55

DO - 10.1007/978-981-95-2382-5_55

M3 - Conference contribution

SN - 978-981-95-2381-8

VL - II

T3 - Lecture Notes in Computer Science (LNCS)

SP - 650

EP - 657

BT - Social Robotics + AI

A2 - Staffa, Mariacarla

A2 - Cabibihan, John-John

A2 - Siciliano, Bruno

A2 - Ge, Shuzhi Sam

A2 - Bodenhagen, Leon

A2 - Tapus, Adriana

A2 - Rossi, Silvia

A2 - Cavallo, Filippo

A2 - Fiorini, Laura

A2 - Matarese, Marco

A2 - He, Hongsheng

PB - Springer

CY - Singapore

T2 - 17th International Conference on Social Robotics + AI, ICSR + AI 2025

Y2 - 10 September 2025 through 12 September 2025

ER -

Pietras E, Salcedo Gil R, Borzone G, Rispens S, Bodenhagen L. Toward Human-Robot Co-learning in Manufacturing. In Staffa M, Cabibihan JJ, Siciliano B, Ge SS, Bodenhagen L, Tapus A, Rossi S, Cavallo F, Fiorini L, Matarese M, He H, editors, Social Robotics + AI: 17th International Conference, ICSR+AI 2025, Naples, Italy, September 10–12, 2025, Proceedings. Vol. II. Singapore: Springer. 2026. p. 650–657. (Lecture Notes in Computer Science (LNCS)). (Lecture Notes in Artificial Intelligence (LNAI)). doi: 10.1007/978-981-95-2382-5_55

Toward Human-Robot Co-learning in Manufacturing

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