Communications of the ACM
Busted for Not Social Distancing by a COVID-19 Mobile Surveillance Robot
The robot is detecting non-compliance to social distancing norms, classifying non-compliant pedestrians into groups and autonomously navigating to the static group with the most people in it (a group with 3 people in this scenario).
Credit: Sathyamoorthy et al.
A new strategy to reduce the spread of COVID-19 employs a mobile robot that detects people in crowds who are not observing social-distancing rules, navigates to them, and encourages them to move apart. Adarsh Jagan Sathyamoorthy of the University of Maryland, College Park, and colleagues present these findings in the open-access journal PLOS ONE on December 1, 2021.
Previous research has shown that staying at least two meters apart from others can reduce the spread of COVID-19. Technology-based methods—such as strategies using WiFi and Bluetooth—hold promise to help detect and discourage lapses in social distancing. However, many such approaches require participation from individuals or existing infrastructure, so robots have emerged as a potential tool for addressing social distancing in crowds.
Now, Sathyamoorthy and colleagues have developed a novel way to use an autonomous mobile robot for this purpose. The robot can detect breaches and navigate to them using its own Red Green Blue—Depth (RGB-D) camera and 2-D LiDAR (Light Detection and Ranging) sensor, and can tap into an existing CCTV system, if available. Once it reaches the breach, the robot encourages people to move apart via text that appears on a mounted display.
From SciTechDaily
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