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Maintaining social distancing norms between humans has become anindispensable precaution to slow down the transmission of COVID-19. We presenta novel method to automatically detect pairs of humans in a crowded scenariowho are not adhering to the social distance constraint, i.e. about 6 feet ofspace between them. Our approach makes no assumption about the crowd density orpedestrian walking directions. We use a mobile robot with commodity sensors,namely an RGB-D camera and a 2-D lidar to perform collision-free navigation ina crowd and estimate the distance between all detected individuals in thecamera's field of view. In addition, we also equip the robot with a thermalcamera that wirelessly transmits thermal images to a security/healthcarepersonnel who monitors if any individual exhibits a higher than normaltemperature. In indoor scenarios, our mobile robot can also be combined withstatic mounted CCTV cameras to further improve the performance in terms ofnumber of social distancing breaches detected, accurately pursuing walkingpedestrians etc. We highlight the performance benefits of our approach indifferent static and dynamic indoor scenarios.

COVID-Robot: Monitoring Social Distancing Constraints in Crowded Scenarios