COVID-19 isolation control proposal via UAV and UGV for crowded indoor environments: Assistive robots in the shopping malls

• Main Authors: Aslan, Muhammet Fatih, Hasikin, Khairunnisa, Yusefi, Abdullah, Durdu, Akif, Sabanci, Kadir, Azizan, Muhammad Mokhzaini
• Format: Article
• Published: Frontiers Media 2022
• Subjects: RA0421 Public health. Hygiene. Preventive Medicine
• Online Access: http://eprints.um.edu.my/41972/

Artificial intelligence researchers conducted different studies to reduce the spread of COVID-19. Unlike other studies, this paper isn't for early infection diagnosis, but for preventing the transmission of COVID-19 in social environments. Among the studies on this is regarding social distancing, as this method is proven to prevent COVID-19 to be transmitted from one to another. In the study, Robot Operating System (ROS) simulates a shopping mall using Gazebo, and customers are monitored by Turtlebot and Unmanned Aerial Vehicle (UAV, DJI Tello). Through frames analysis captured by Turtlebot, a particular person is identified and followed at the shopping mall. Turtlebot is a wheeled robot that follows people without contact and is used as a shopping cart. Therefore, a customer doesn't touch the shopping cart that someone else comes into contact with, and also makes his/her shopping easier. The UAV detects people from above and determines the distance between people. In this way, a warning system can be created by detecting places where social distance is neglected. Histogram of Oriented-Gradients (HOG)-Support Vector Machine (SVM) is applied by Turtlebot to detect humans, and Kalman-Filter is used for human tracking. SegNet is performed for semantically detecting people and measuring distance via UAV. This paper proposes a new robotic study to prevent the infection and proved that this system is feasible.