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Register a new userAn Analysis of International Use of Robots for COVID-19
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Vignesh Babu Manjunath Gandudi
Publication date
2021
fields
Informatics Engineering
and research's language is
English
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This article analyses data collected on 338 instances of robots used explicitly in response to COVID-19 from 24 Jan, 2020, to 23 Jan, 2021, in 48 countries. The analysis was guided by four overarching questions: 1) What were robots used for in the COVID-19 response? 2) When were they used? 3) How did different countries innovate? and 4) Did having a national policy on robotics influence a countrys innovation and insertion of robotics for COVID-19? The findings indicate that robots were used for six different sociotechnical work domains and 29 discrete use cases. When robots were used varied greatly on the country; although many countries did report an increase at the beginning of their first surge. To understand the findings of how innovation occurred, the data was examined through the lens of the technologys maturity according to NASAs Technical Readiness Assessment metrics. Through this lens, findings note that existing robots were used for more than 78% of the instances; slightly modified robots made up 10%; and truly novel robots or novel use cases constituted 12% of the instances. The findings clearly indicate that countries with a national robotics initiative were more likely to use robotics more often and for broader purposes. Finally, the dataset and analysis produces a broad set of implications that warrant further study and investigation. The results from this analysis are expected to be of value to the robotics and robotics policy community in preparing robots for rapid insertion into future disasters.
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This paper reviews 262 reports appearing between March 27 and July 4, 2020, in the press, social media, and scientific literature describing 203 instances of actual use of 104 different models of ground and aerial robots for the COVID19 response. The reports are organized by stakeholders and work domain into a novel taxonomy of six application categories, reflecting major differences in work envelope, adoption strategy, and human-robot interaction constraints. Each application category is further divided into a total of 30 subcategories based on differences in mission. The largest number of reported instances were for public safety (74 out of 203) and clinical care (46), though robots for quality of life (27), continuity of work and education (22), laboratory and supply chain automation (21), and non-clinical care (13) were notable. Ground robots were used more frequently (119) than aerial systems (84), but unlike ground robots, aerial applications appeared to take advantage of existing general purpose platforms that were used for multiple applications and missions. Of the 104 models of robots, 82 were determined to be commercially available or already existed as a prototype, 11 were modifications to existing robots, 11 were built from scratch. Teleoperation dominated the control style (105 instances), with the majority of those applications intentionally providing remote presence and thus not amenable to full autonomy in the future. Automation accounted for 74 instances and taskable agency forms of autonomy, 24. The data suggests areas for further research in autonomy, human-robot interaction, and adaptability.
Medical robots can play an important role in mitigating the spread of infectious diseases and delivering quality care to patients during the COVID-19 pandemic. Methods and procedures involving medical robots in the continuum of care, ranging from disease prevention, screening, diagnosis, treatment, and homecare have been extensively deployed and also present incredible opportunities for future development. This paper provides an overview of the current state-of-the-art, highlighting the enabling technologies and unmet needs for prospective technological advances within the next 5-10 years. We also identify key research and knowledge barriers that need to be addressed in developing effective and flexible solutions to ensure preparedness for rapid and scalable deployment to combat infectious diseases.
The COVID-19 pandemic has disrupted human activities, leading to unprecedented decreases in both global energy demand and GHG emissions. Yet a little known that there is also a low carbon shift of the global energy system in 2020. Here, using the near-real-time data on energy-related GHG emissions from 30 countries (about 70% of global power generation), we show that the pandemic caused an unprecedented de-carbonization of global power system, representing by a dramatic decrease in the carbon intensity of power sector that reached a historical low of 414.9 tCO2eq/GWh in 2020. Moreover, the share of energy derived from renewable and low-carbon sources (nuclear, hydro-energy, wind, solar, geothermal, and biomass) exceeded that from coal and oil for the first time in history in May of 2020. The decrease in global net energy demand (-1.3% in the first half of 2020 relative to the average of the period in 2016-2019) masks a large down-regulation of fossil-fuel-burning power plants supply (-6.1%) coincident with a surge of low-carbon sources (+6.2%). Concomitant changes in the diurnal cycle of electricity demand also favored low-carbon generators, including a flattening of the morning ramp, a lower midday peak, and delays in both the morning and midday load peaks in most countries. However, emission intensities in the power sector have since rebounded in many countries, and a key question for climate mitigation is thus to what extent countries can achieve and maintain lower, pandemic-level carbon intensities of electricity as part of a green recovery.
Novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become a pandemic of epic proportions and a global response to prepare health systems worldwide is of utmost importance. In addition to its cost-effectiveness in a resources-limited setting, lung ultrasound (LUS) has emerged as a rapid noninvasive imaging tool for the diagnosis of COVID-19 infected patients. Concerns surrounding LUS include the disparity of infected patients and healthcare providers, relatively small number of physicians and sonographers capable of performing LUS, and most importantly, the requirement for substantial physical contact between the patient and operator, increasing the risk of transmission. Mitigation of the spread of the virus is of paramount importance. A 2-dimensional (2D) tele-operative robotic platform capable of performing LUS in for COVID-19 infected patients may be of significant benefit. The authors address the aforementioned issues surrounding the use of LUS in the application of COVID- 19 infected patients. In addition, first time application, feasibility and safety were validated in three healthy subjects, along with 2D image optimization and comparison for overall accuracy. Preliminary results demonstrate that the proposed platform allows for successful acquisition and application of LUS in humans.
The paper addresses the question of lives versus livelihood in an SIRD model augmented with a macroeconomic structure. The constraints on the availability of health facilities - both infrastructure and health workers determine the probability of receiving treatment which is found to be higher for the patients with severe infection than the patients with mild infection for the specific parametric configuration of the paper. Distinguishing between two types of direct intervention policy - hard lockdown and soft lockdown, the study derives alternative policy options available to the government. The study further indicates that the soft lockdown policy is optimal from a public policy perspective under the specific parametric configuration considered in this paper.
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