Deploying collaborative robots in manufacturing presents diverse challenges. Rapid adaptability to the environment while ensuring user safety and engagement is paramount. Existing human-aware task sequencing solutions often lack explicit risk modeling and management. International standards emphasize severity, exposure, and avoidance as critical risk factors. To enhance intelligent risk awareness control, we propose integrating multiple risk factors into task sequencing models. This forms the basis for a cutting-edge planning framework-backed risk-aware task sequencing system. Our approach’s evaluation across various scenarios showcases its efficacy and adaptability to diverse risk levels. Experimental results show a positive equilibrium between productivity and safety, achieving both high throughput and low operator risk.

Risk-Aware Task Sequencing for Human-Robot Collaboration

Cesta A.;Orlandini A.
;
Umbrico A.
2024

Abstract

Deploying collaborative robots in manufacturing presents diverse challenges. Rapid adaptability to the environment while ensuring user safety and engagement is paramount. Existing human-aware task sequencing solutions often lack explicit risk modeling and management. International standards emphasize severity, exposure, and avoidance as critical risk factors. To enhance intelligent risk awareness control, we propose integrating multiple risk factors into task sequencing models. This forms the basis for a cutting-edge planning framework-backed risk-aware task sequencing system. Our approach’s evaluation across various scenarios showcases its efficacy and adaptability to diverse risk levels. Experimental results show a positive equilibrium between productivity and safety, achieving both high throughput and low operator risk.
2024
Istituto di Scienze e Tecnologie della Cognizione - ISTC
9783031574955
9783031574962
Human-Robot Collaboration
Artificial Intelligence
Task Planning and Scheduling
File in questo prodotto:
File Dimensione Formato  
ESAIM23 CR FINAL.pdf

accesso aperto

Descrizione: Bonini, A., Cesta, A., Cialdea Mayer, M., Orlandini, A., Umbrico, A. (2024). Risk-Aware Task Sequencing for Human-Robot Collaboration. In: Wagner, A., Alexopoulos, K., Makris, S. (eds) Advances in Artificial Intelligence in Manufacturing. ESAIM 2023. Lecture Notes in Mechanical Engineering. Springer, Cham. https://biblioproxy.cnr.it:2481/10.1007/978-3-031-57496-2_15
Tipologia: Documento in Pre-print
Licenza: Creative commons
Dimensione 540.35 kB
Formato Adobe PDF
540.35 kB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/515269
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 0
  • ???jsp.display-item.citation.isi??? 0
social impact