Humans and robots are increasingly sharing theirworkspaces to benefit from the precision, endurance, andstrength of machines and the universal capabilities of humans.Instead of performing time-consuming real experiments, com-puter simulations of humans could help to optimally orchestratehuman and robotic tasks—either for setting up new productioncells or by optimizing the motion planning of already installedrobots. Especially when human-robot coexistence is optimizedusing machine learning, being able to synthesize a huge numberof human motions is indispensable. However, no solution existsthat automatically creates a range of human motions from ahigh-level specification of tasks. We propose a novel method thatautomatically generates human motions from linear temporallogic specifications and demonstrate our approach by numericalexamples.     «

Humans and robots are increasingly sharing theirworkspaces to benefit from the precision, endurance, andstrength of machines and the universal capabilities of humans.Instead of performing time-consuming real experiments, com-puter simulations of humans could help to optimally orchestratehuman and robotic tasks—either for setting up new productioncells or by optimizing the motion planning of already installedrobots. Especially when human-robot coexistence is optimizedusi...     »