This paper studies the problem of safe humanuncrewed aerial system (UAS) collaboration in a shared work environment. By considering human and UAS as co-workers, we use Petri Nets to abstractly model evolution of shared tasks assigned to human and UAS co-workers. Particularly, the Petri Nets places represent work stations; therefore, the Petri Nets transitions can formally specify displacements between the work stations. The first objective is to incorporate uncertainty regarding the intentions of human co-workers into motion planning for UAS, when UAS co-workers closely interact with human co-workers. To this end, the proposed Petri Nets model uses conflict constructs to represent situations at which UAS deals with incomplete knowledge about human co-worker intention. The second objective is then to plan the motion of the UAS in a resilient and safe manner, in the presence of non-cooperative human co-workers. In order to achieve this objective, UAS equipped with onboard perception and decision-making capabilities are able to, through real-time processing of in-situ observation, predict human intention, quantify human distraction, and apply a non-stationary Markov Decision model to safely plan UAS motion in the presence of uncertainty.