Primož Bencak (Avtor), Darko Hercog (Avtor), Tone Lerher (Avtor)

Povzetek

Robotics has been gaining attention in intralogistics applications in recent years. Automation of intralogistics processes aims to cope with the rising trends of workforce deficiency, aging, and increasing demands that came with the rise of E-commerce. Many improvements aim at bin-picking applications since order-picking requires most contributions while adding little to the products' value. Robotic bin-pickers are showing promising results; however, they are still subject to many limitations. First, the vision system must correctly determine the object's location and orientation. Second, a correct robotic gripper must be chosen. Lastly, appropriate grasping points that lead to successful picking must be selected. In this paper, we explore the influencing parameters of object detection using a 3D vision system. Second, we analyze an actual bin-picking application to determine the most appropriate selection of the robotic gripper. Based on the experiments, we provide the guidelines for selecting the most appropriate robotic bin-picking configuration.

Ključne besede

intralogistics;robotic bin-picking;detection analysis;graspability analysis;

Podatki

Jezik: Angleški jezik
Leto izida:
Tipologija: 1.08 - Objavljeni znanstveni prispevek na konferenci
Organizacija: UM FL - Fakulteta za logistiko
Založnik: University of Zagreb, Faculty of Mechanical Engineering and Naval Architecture
UDK: 658:007.52
COBISS: 154849795 Povezava se bo odprla v novem oknu
Št. ogledov: 134
Št. prenosov: 5
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: intralogistika;robotsko komisioniranje;analiza detekcije;analiza oprijemljivosti;
Vrsta dela (COBISS): Drugo
Strani: Str. 7-14
ID: 19638692
Priporočena dela:
, benchmarking robotics grippers with modified YCB object and model set
, diplomsko delo univerzitetnega študijskega programa