Nejc Kozamernik (Avtor), Janez Zaletelj (Avtor), Andrej Košir (Avtor), Filip Šuligoj (Avtor), Drago Bračun (Avtor)

Povzetek

Efficient workspace awareness is critical for improved interaction in cooperative and collaborative robotic applications. In addition to safety and control aspects, quality-related tasks such as the monitoring of manual activities and the final quality assessment of the results are also required. In this context, a visual quality and safety monitoring system is developed and evaluated. The system integrates close-up observation of manual activities and posture monitoring. A compact single-camera stereo vision system and a time-of-flight depth camera are used to minimize the interference of the sensors with the operator and the workplace. Data processing is based on a deep learning to detect classes related to quality and safety aspects. The operation of the system is evaluated while monitoring a human-robot manual assembly task. The results show that the system ensures a high level of safety, provides reliable visual feedback to the operator on errors in the assembly process, and inspects the finished assembly with a low critical error rate.

Ključne besede

human-robot cooperation;vision systems;quality;safety;assembly supervision;

Podatki

Jezik: Angleški jezik
Leto izida:
Tipologija: 1.01 - Izvirni znanstveni članek
Organizacija: UL FS - Fakulteta za strojništvo
UDK: 007.52
COBISS: 159531011 Povezava se bo odprla v novem oknu
ISSN: 0268-3768
Št. ogledov: 15
Št. prenosov: 3
Ocena: 0 (0 glasov)
Metapodatki: JSON JSON-RDF JSON-LD TURTLE N-TRIPLES XML RDFA MICRODATA DC-XML DC-RDF RDF

Ostali podatki

Sekundarni jezik: Slovenski jezik
Sekundarne ključne besede: sodelovanje človek-robot;slikovni sistemi;varnost;kakovost;nadzor sestavljanja;
Vrsta dela (COBISS): Članek v reviji
Strani: str. 1-17
Čas izdaje: Jul. 2023
DOI: 10.1007/s00170-023-11698-2
ID: 21281413
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