The use of autonomous systems in Intensive Care Units (ICUs) has become incredibly important, especially during the COVID-19 pandemic. This period has overwhelmed both ICUs and hospitals, halting many other medical activities and causing significant challenges. This project aims to develop a navigation system tailored specifically for the ICU environment, adapting it to the unique procedures and regulations of that setting. Due to the critical conditions of ICU patients, strict rules dictate precise requirements for navigation, necessitating a context-specific approach. This work will propose a comprehensive navigation system capable of safely guiding from point A to point B within an ICU while addressing the critical issues present in such environments. Unlike traditional Nav2 systems, it will feature specialized collision avoidance components designed specifically for ICU settings, taking into account both contextual demands and the chosen approach. This will involve implementing a multilayered protection technique and employing active movements to prevent collisions with dynamic obstacles.

Enhancing Efficiency and Safety Through Autonomous Navigation in the Intensive Care Unit / Ponzi, Valerio; Puglisi, Adriano. - 3684:(2023), pp. 60-69. (Intervento presentato al convegno 8th International Conference of Yearly Reports on Informatics, Mathematics, and Engineering, ICYRIME 2023 tenutosi a Napoli; Italia).

Enhancing Efficiency and Safety Through Autonomous Navigation in the Intensive Care Unit

Valerio Ponzi
Co-primo
Investigation
;
Adriano Puglisi
Co-primo
Investigation
2023

Abstract

The use of autonomous systems in Intensive Care Units (ICUs) has become incredibly important, especially during the COVID-19 pandemic. This period has overwhelmed both ICUs and hospitals, halting many other medical activities and causing significant challenges. This project aims to develop a navigation system tailored specifically for the ICU environment, adapting it to the unique procedures and regulations of that setting. Due to the critical conditions of ICU patients, strict rules dictate precise requirements for navigation, necessitating a context-specific approach. This work will propose a comprehensive navigation system capable of safely guiding from point A to point B within an ICU while addressing the critical issues present in such environments. Unlike traditional Nav2 systems, it will feature specialized collision avoidance components designed specifically for ICU settings, taking into account both contextual demands and the chosen approach. This will involve implementing a multilayered protection technique and employing active movements to prevent collisions with dynamic obstacles.
2023
8th International Conference of Yearly Reports on Informatics, Mathematics, and Engineering, ICYRIME 2023
Autonomous navigation; Collision avoidance; Artificial Intelligence; Reinforcement Learning
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
Enhancing Efficiency and Safety Through Autonomous Navigation in the Intensive Care Unit / Ponzi, Valerio; Puglisi, Adriano. - 3684:(2023), pp. 60-69. (Intervento presentato al convegno 8th International Conference of Yearly Reports on Informatics, Mathematics, and Engineering, ICYRIME 2023 tenutosi a Napoli; Italia).
File allegati a questo prodotto
File Dimensione Formato  
Ponzi_Enhacing-Efficiency_2023.pdf

accesso aperto

Note: https://ceur-ws.org/Vol-3684/p10.pdf
Tipologia: Versione editoriale (versione pubblicata con il layout dell'editore)
Licenza: Creative commons
Dimensione 1.28 MB
Formato Adobe PDF
1.28 MB Adobe PDF

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/11573/1715962
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 0
  • ???jsp.display-item.citation.isi??? ND
social impact