Robot assistants and professional coworkers are becoming a commodity in domestic and industrial settings. In order to enable robots to share their workspace with humans and physically interact with them, fast and reliable handling of possible collisions on the entire robot structure is needed, along with control strategies for safe robot reaction. The primary motivation is the prevention or limitation of possible human injury due to physical contacts. In this survey paper, based on our early work on the subject, we review, extend, compare, and evaluate experimentally model-based algorithms for real-time collision detection, isolation, and identification that use only proprioceptive sensors. This covers the context-independent phases of the collision event pipeline for robots interacting with the environment, as in physical human-robot interaction or manipulation tasks. The problem is addressed for rigid robots first and then extended to the presence of joint/transmission flexibility. The basic physically motivated solution has already been applied to numerous robotic systems worldwide, ranging from manipulators and humanoids to flying robots, and even to commercial products.

Robot Collisions: A Survey on Detection, Isolation, and Identification / Haddadin, Sami; De Luca, Alessandro; Albu-Schaffer, Alin. - In: IEEE TRANSACTIONS ON ROBOTICS. - ISSN 1552-3098. - 33:6(2017), pp. 1292-1312. [10.1109/TRO.2017.2723903]

Robot Collisions: A Survey on Detection, Isolation, and Identification

De Luca, Alessandro
;
2017

Abstract

Robot assistants and professional coworkers are becoming a commodity in domestic and industrial settings. In order to enable robots to share their workspace with humans and physically interact with them, fast and reliable handling of possible collisions on the entire robot structure is needed, along with control strategies for safe robot reaction. The primary motivation is the prevention or limitation of possible human injury due to physical contacts. In this survey paper, based on our early work on the subject, we review, extend, compare, and evaluate experimentally model-based algorithms for real-time collision detection, isolation, and identification that use only proprioceptive sensors. This covers the context-independent phases of the collision event pipeline for robots interacting with the environment, as in physical human-robot interaction or manipulation tasks. The problem is addressed for rigid robots first and then extended to the presence of joint/transmission flexibility. The basic physically motivated solution has already been applied to numerous robotic systems worldwide, ranging from manipulators and humanoids to flying robots, and even to commercial products.
2017
collision detection; collision identification; collision isolation; flexible joint manipulators; human-friendly robotics; monitoring; physical human–robot interaction (pHRI); safe robotics
01 Pubblicazione su rivista::01a Articolo in rivista
Robot Collisions: A Survey on Detection, Isolation, and Identification / Haddadin, Sami; De Luca, Alessandro; Albu-Schaffer, Alin. - In: IEEE TRANSACTIONS ON ROBOTICS. - ISSN 1552-3098. - 33:6(2017), pp. 1292-1312. [10.1109/TRO.2017.2723903]
File allegati a questo prodotto
File Dimensione Formato  
Haddadin_Robot-Collisions_2017.pdf

solo gestori archivio

Tipologia: Versione editoriale (versione pubblicata con il layout dell'editore)
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 2.07 MB
Formato Adobe PDF
2.07 MB Adobe PDF   Contatta l'autore
Haddadin_Postprint_Robot-Collisions_2017.pdf

accesso aperto

Note: DOI: 10.1109/TRO.2017.2723903
Tipologia: Documento in Post-print (versione successiva alla peer review e accettata per la pubblicazione)
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 2.1 MB
Formato Adobe PDF
2.1 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/11573/1071580
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 484
  • ???jsp.display-item.citation.isi??? 366
social impact