Let Human-Robot Motion (HRM) denote the study of how robots should move among people, the work presented herein explores to what extent human attention can be useful to address HRM. To that end, a computational model of the human visual attention is proposed, it determines how a person's attentional resources are distributed among the items in her/his environment. Based on this model, the concept of attention field for a robot is developed and then used to define different attentional properties for the robot's motions such as distraction or surprise. Said attentional properties are finally exploited to design an acceptable motion planner capable of computing motions that are non-distracting and non-surprising, but also paths that convey the robot's intention to interact with a person.