PORTO @ 
Archivio Istituzionale della Ricerca
IRIS è la soluzione IT che facilita la raccolta e la gestione dei dati relativi alle attività e ai prodotti della ricerca. Fornisce a ricercatori, amministratori e valutatori gli strumenti per monitorare i risultati della ricerca, aumentarne la visibilità e allocare in modo efficace le risorse disponibili.
EnglishIn smart factories, the performance of the production lines is improved thanks to the wide application of mobile robots. In workspaces where human operators and mobile robots coexist, safety is a fundamental factor to be considered. In this context, the motion planning of Autonomous Mobile Robots is a challenging task, since it must take into account the human factor. In this paper, an implementation of a three-level online path planning is proposed, in which a set of waypoints belonging to a safe path is computed by a supervisory planner. Depending on the nature of the detected obstacles during the robot motion, the re-computation of the safe path may be enabled, after the collision avoidance action provided by the local planner is initiated. Particular attention is devoted to the detection and avoidance of human operators. The supervisory planner is triggered as the detected human gets sufficiently close to the mobile robot, allowing it to follow a new safe virtual path while conservatively circumnavigating the operator. The proposed algorithm has been experimentally validated in a laboratory environment emulating industrial scenarios.
Online supervised global path planning for AMRs with human-obstacle avoidance / Indri, Marina; Sibona, Fiorella; Cen Cheng, Pangcheng David; Possieri, Corrado. - ELETTRONICO. - (2020), pp. 1473-1479. ((Intervento presentato al convegno 25th IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2020 tenutosi a Vienna, Austria nel 08-11 September 2020.
Scheda prodotto non validato
Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo
| Titolo: | Online supervised global path planning for AMRs with human-obstacle avoidance |
| Autori: | |
| Data di pubblicazione: | 2020 |
| Abstract: | In smart factories, the performance of the production lines is improved thanks to the wide applic...ation of mobile robots. In workspaces where human operators and mobile robots coexist, safety is a fundamental factor to be considered. In this context, the motion planning of Autonomous Mobile Robots is a challenging task, since it must take into account the human factor. In this paper, an implementation of a three-level online path planning is proposed, in which a set of waypoints belonging to a safe path is computed by a supervisory planner. Depending on the nature of the detected obstacles during the robot motion, the re-computation of the safe path may be enabled, after the collision avoidance action provided by the local planner is initiated. Particular attention is devoted to the detection and avoidance of human operators. The supervisory planner is triggered as the detected human gets sufficiently close to the mobile robot, allowing it to follow a new safe virtual path while conservatively circumnavigating the operator. The proposed algorithm has been experimentally validated in a laboratory environment emulating industrial scenarios. |
| Appare nelle tipologie: | 4.1 Contributo in Atti di convegno |
File in questo prodotto:
| File | Descrizione | Tipologia | Licenza | |
|---|---|---|---|---|
| ETFA_RTT_2020.pdf | Published version | 2a Post-print versione editoriale / Version of Record | Non Pubblico - Accesso privato/ristretto | Administrator Richiedi una copia |
| Final_author_version.pdf | Authors' version | 2. Post-print / Author's Accepted Manuscript | PUBBLICO - Tutti i diritti riservati | Visibile a tuttiVisualizza/Apri |
http://hdl.handle.net/11583/2846370
Copyright © 2021