High-speed motion tracking and coupling for human-robot collaborative assembly tasks (HiSMoT)

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Human-robot collaboration (HRC) combines the capabilities of humans and robots in order to create a more inclusive and human-centered future in the production industry. The capabilities of HRC have been investigated extensively for manufacturing processes, mainly in laboratory environments. However, they are not widely applied in production systems. Performance and safety can be a primary challenge that limits collaboration efficiency, particularly for motions at higher speeds. The collaborative handling of an object is one of the current challenges facing HRC's real collaboration capabilities. In this context, how robots and humans should behave to handle an object and anticipate motion for mutual care is still unclear. One approach is to create robot motions that avoid risks to human body parts caused by high speeds of the robot tool center point (TCP), which might result from reactions to human motions. Coupling motion models for such approaches is difficult because unlike industrial robots, human motion is not easily modeled using geometric or analytical formulations such as rigid body dynamics. Instead, data-driven models for human motion generation are employed in various research and industrial applications such as sports, health, film, ergonomics and production. This research project investigates real-time capable approaches to coupling data driven human motion models with robot motion models in HRC applications. The project concentrates on the collaborative handling of rigid parts. In real time modeling, high speed motions are considered. A central research question is whether and in what way human and robot motion models can be coupled and implemented using motion capture-driven approaches. In this context, latent space control approaches are investigated for the capability to follow the high mutual support and anticipation principle. With the evolving concept of a personalized production system, speed, accuracy, agility and controllability are key parameters. In this regard, HRC may have the potential to narrow a gap in the automation of product assembly systems.