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COVID-19

RoboCop-style COVID bot hunts for people not social distancing

"The robot uses a novel system to sort people who have breached social distancing rules into different groups, prioritize them according to whether they are standing still or moving, and then navigate to them."'

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By Stephen Beech via SWNS

A new Robocop-style Covid bot hunts down people breaking social distancing rules.

The surveillance robot could help reduce the spread of the virus and also aid contact tracing, say scientists.

They explained how the mobile robot detects people in crowds who are not observing social-distancing rules, navigates to them, and "encourages" them to move apart.

"Previous research has shown that staying at least two meters apart from others can reduce the spread of COVID-19," said study lead author Adarsh Jagan Sathyamoorthy.

"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 his colleagues have developed a new way to use an autonomous mobile robot for that purpose.

He said the robot can detect breaches and navigate to them using its own camera and 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,"said Sathyamoorthy, a PhD student specializing in robotics.

"The robot uses a novel system to sort people who have breached social distancing rules into different groups, prioritize them according to whether they are standing still or moving, and then navigate to them."'

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. (Sathyamoorthy et al. via SWNS).

He said the system employs a machine-learning method known as Deep Reinforcement Learning and Frozone, an algorithm previously developed by several of the same researchers to help robots navigate crowds.

The researchers tested their method by having volunteers act out social-distancing breach scenarios while standing still, walking, or moving erratically.

Their robot was able to detect and address most of the breaches that occurred, and CCTV enhanced its performance.

"The robot also uses a thermal camera that can detect people with potential fevers, aiding contact-tracing efforts, while also incorporating measures to ensure privacy protection and de-identification,"Sathyamoorthy said.

He said further research is needed to validate and refine the system, such as looking at how the presence of robots impacts people’s behaviour in crowds.

"A lot of healthcare workers and security personnel had to put their health at risk to serve the public during the Covid-19 pandemic," he added.

"Our work's core objective is to provide them with tools to safely and efficiently serve their communities."

The findings were published in the journal PLoS One.

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