Individualization of digital human models for planning of human–robot collaboration

Abstract In this chapter, the use of digital human modeling systems (DHM systems) for the individualization of human–robot collaboration is described. Usually, DHM systems use predefined manikins, sizes of which are based on percentile tables of a specific population. This is the current state-of-the-art approach to accommodate the majority of the targeted population within virtual human simulations. Another approach is the use of boundary manikins of the targeted population. Recent developments in sensor technologies, the increased digital interconnectivity, and increasingly adaptive workplace assistance systems facilitate a finer graduated use of human parameters. In addition to anthropometric data, even kinematic parameters, such as range of motion, could be taken into consideration. Hence, to improve the individualization of direct human–robot collaboration, in-depth knowledge of the anthropometric and kinematic profile of the employee is beneficial. Measuring anthropometric and kinematic data manually is time-consuming and expensive and, therefore, not suitable as a standard process. A digital assessment with new technologies, for instance, markerless motion capturing or 3D body scanning, is preferable. The digitally assessed parameters can be used to scale and parametrize a DHM system. Within a subsequent simulation with integrated ergonomic assessment, the individualized DHM system is then able to consider even unusual body compositions or individuals with impairments. The outcome of such a virtual analysis fosters the human-centered optimization within the prospective workplace design, especially for workplaces incorporating collaborative robots.