TY - JOUR
T1 - Interactive Process Automation based on lightweight object detection in manufacturing processes
AU - Mangat, Amolkirat Singh
AU - Mangler, Juergen
AU - Rinderle-Ma, Stefanie
N1 - Publisher Copyright:
© 2021
PY - 2021/9
Y1 - 2021/9
N2 - Interactive Process Automation refers to the idea of supporting the interaction of humans in processes through physical objects. This is particularly promising for human/cobot collaboration tasks where the communication is fuzzy. A typical example is a picking and placing scenario. Here, a “picking area” can serve as a user interface, i.e., objects are freely placed in a defined area, and then identified and transferred to specific positions, where deterministic processes can use them. If, for example, object A is placed at position posA by the human, automatically, the robot is instructed to pick A and place it at position posB on a tray. Realizing Interactive Process Automation for picking and placing tasks in manufacturing processes requires (i) a lightweight and flexible object detection approach and (ii) a human–machine interface design for Interactive Process Automation. This work proposes (i) an object detection approach that works solely based on synthetic training data. The object detection is embedded into (ii) generic process models that are implemented based on an existing manufacturing orchestration framework and a camera-equipped cobot. The approach is prototypically implemented and evaluated based on several experiments including a pick and place cobot station.
AB - Interactive Process Automation refers to the idea of supporting the interaction of humans in processes through physical objects. This is particularly promising for human/cobot collaboration tasks where the communication is fuzzy. A typical example is a picking and placing scenario. Here, a “picking area” can serve as a user interface, i.e., objects are freely placed in a defined area, and then identified and transferred to specific positions, where deterministic processes can use them. If, for example, object A is placed at position posA by the human, automatically, the robot is instructed to pick A and place it at position posB on a tray. Realizing Interactive Process Automation for picking and placing tasks in manufacturing processes requires (i) a lightweight and flexible object detection approach and (ii) a human–machine interface design for Interactive Process Automation. This work proposes (i) an object detection approach that works solely based on synthetic training data. The object detection is embedded into (ii) generic process models that are implemented based on an existing manufacturing orchestration framework and a camera-equipped cobot. The approach is prototypically implemented and evaluated based on several experiments including a pick and place cobot station.
KW - Deep learning
KW - Interactive Process Automation
KW - Manufacturing processes
KW - Object detection
KW - Synthetic training images
UR - http://www.scopus.com/inward/record.url?scp=85105745291&partnerID=8YFLogxK
U2 - 10.1016/j.compind.2021.103482
DO - 10.1016/j.compind.2021.103482
M3 - Article
AN - SCOPUS:85105745291
SN - 0166-3615
VL - 130
JO - Computers in Industry
JF - Computers in Industry
M1 - 103482
ER -