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Journal Articles IEEE Robotics and Automation Letters Year : 2019

Using Human Attention to Address Human-Robot Motion

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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 to estimate how a person's attentional resources are distributed among the elements in their environment. Based on this model, the concept of attention field for a robot is used to define different attentional properties for the robot's motions such as distraction or surprise. The relevance of the attentional properties for HRM are demonstrated on a proof-of-concept acceptable motion planner on various case studies where a robot is assigned different tasks. It is shown how to compute motions that are non-distracting and non-surprising, but also motions that convey the robot's intention to interact with a person.
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hal-02013578 , version 1 (11-02-2019)
hal-02013578 , version 2 (11-02-2019)



Remi Paulin, Thierry Fraichard, Patrick Reignier. Using Human Attention to Address Human-Robot Motion. IEEE Robotics and Automation Letters, 2019, 4 (2), pp.2038-2045. ⟨10.1109/LRA.2019.2899429⟩. ⟨hal-02013578v2⟩
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