COVID surveillance robot: Monitoring social distancing constraints in indoor scenarios.

Journal: PloS one
PMID:

Abstract

Observing social/physical distancing norms between humans has become an indispensable precaution to slow down the transmission of COVID-19. We present a novel method to automatically detect pairs of humans in a crowded scenario who are not maintaining social distancing, i.e. about 2 meters of space between them using an autonomous mobile robot and existing CCTV (Closed-Circuit TeleVision) cameras. The robot is equipped with commodity sensors, namely an RGB-D (Red Green Blue-Depth) camera and a 2-D lidar to detect social distancing breaches within their sensing range and navigate towards the location of the breach. Moreover, it discreetly alerts the relevant people to move apart by using a mounted display. In addition, we also equip the robot with a thermal camera that transmits thermal images to security/healthcare personnel who monitors COVID symptoms such as a fever. In indoor scenarios, we integrate the mobile robot setup with a static wall-mounted CCTV camera to further improve the number of social distancing breaches detected, accurately pursuing walking groups of people etc. We highlight the performance benefits of our robot + CCTV approach in different static and dynamic indoor scenarios.

Authors

  • Adarsh Jagan Sathyamoorthy
    Department of Electrical and Computer Engineering, University of Maryland, College Park, Maryland, United States of America.
  • Utsav Patel
    Department of Computer Science, University of Maryland, College Park, Maryland, United States of America.
  • Moumita Paul
    Institute of Systems Research, University of Maryland, College Park, Maryland, United States of America.
  • Yash Savle
    Institute of Systems Research, University of Maryland, College Park, Maryland, United States of America.
  • Dinesh Manocha