Detection and Identification of Assembly Characteristics of Lithium-Ion Battery Modules Using RGB-D Imagery

A large diversity of product variants often leads to decision making problems during product and assembly process development. This paper presents a novel method that is used to quickly gather assembly characteristics of product variants for the enrichment of criteria for decision making methods and acceleration of assembly process planning. The collection of data is accomplished through a depth camera-based surveillance of a flexible, reconfigurable assembly workspace. For the surveillance, a robust and efficient motion tracking approach is developed theoretically and implemented practically in a software environment. The evaluation of the presented method is done by assembling different lithium-ion battery variants.