Retroactive about Robotics Application with Artificial Intelligence toward the Global Pandemic Scenario

Abstract

The COVID-19 pandemic affects the entire world and took about 4.25% of people’s life compared with SARS-CoV-2. In this challenging situation about 25,000 frontline healthcare workers are affected by COVID-19 while providing support for the infected people. Hence, frontline workers are highly affected by the COVID-19 virus due to the absence of appropriate drugs or vaccines. The increase in the spread of the virus leads to a shortage of healthcare workers in different countries. In this scenario, to protect the frontline workers from the COVID-19 virus robots integrated with Artificial Intelligence are employed for pandemic diseases. This paper evaluated the contribution of robotics to the COVID-19 pandemic which comprises Artificial Intelligence. Initially, this paper presented the existing robotics model employed for the COVID-19 pandemics are examined. Through the analysis, the Simultaneous Fast Filtering Localization and Mapping (SFFLAM) model is developed for the hospital environment to promote frontline worker safety in the COVID-19 pandemic. The proposed SFFLAM model uses the extended Kalman filtering integrated with the sectorial error probability (SEP) for robot localization. The examination of robots expressed that through the integration of artificial intelligence robots are employed for the medical, UV-disinfectant, social, COBOTS, and drones. The examination expresses that the proposed SFFLAM model exhibits improved robotics performance for localization and processing. The application of robots with artificial intelligence increases the performance of the overall robot in the hospital during pandemic situations.