KIT | KIT-Bibliothek | Impressum | Datenschutz

Seeing ahead through a state-of-the-art review of visual perception and predictive intelligence for collaborative robots

Salem, Mahmoud ORCID iD icon 1; Reischl, Markus ORCID iD icon 1; Hagenmeyer, Veit ORCID iD icon 1; Nau, Katja ORCID iD icon 1; Elkaseer, Ahmed 1
1 Institut für Automation und angewandte Informatik (IAI), Karlsruher Institut für Technologie (KIT)

Abstract:

The rate at which collaborative robots (cobots) are evolving from isolated, pre-programmed manipulators into collaborative partners that operate productively alongside humans, other robots, and machines is accelerating rapidly. Advances in computer vision is enabling cobots, even in dynamic and cluttered settings, to detect, recognise and assess both environment and actions. However, achieving higher detection accuracy and real-time localization in dynamic systems remains a challenge, as most existing approaches assume uncluttered backgrounds with limited scene complexity. Closing this gap is critical for both research and industrial deployment. This paper reviews the development of visual perception in cobots, surveys emerging computer vision algorithms, and examines a holistic perception pipeline in which raw vision signals, vision language models (VLMs), and augmented/virtual reality interfaces jointly power a unified sense-think-act loop. The review finds that cobots in high-mix, reconfigurable factories face serious challenges: occlusions in fields of view, fluctuating illumination, ambiguous backgrounds, few- or zero-shot object scenarios, high-speed motion, and computational problems in fusing heterogeneous data streams in real time. ... mehr


Verlagsausgabe §
DOI: 10.5445/IR/1000198076
Veröffentlicht am 19.10.2026
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Automation und angewandte Informatik (IAI)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2026
Sprache Englisch
Identifikator ISSN: 1573-7462
KITopen-ID: 1000198076
HGF-Programm 43.31.02 (POF IV, LK 01) Devices and Applications
Erschienen in Artificial Intelligence Review
Verlag Springer
Band 59
Heft 12
Seiten Art.Nr: 253
Vorab online veröffentlicht am 17.10.2026
Nachgewiesen in OpenAlex
Web of Science
Scopus
KIT – Die Universität in der Helmholtz-Gemeinschaft
KITopen Landing Page