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1. Demographics and Automation

   https://doi.org/10.1093/restud/rdab031  

   Acemoglu, Daron; Restrepo, Pascual (June 2021, The Review of Economic Studies)

   Krueger, Dirk (Ed.)

   Abstract We argue theoretically and document empirically that aging leads to greater (industrial) automation, because it creates a shortage of middle-aged workers specializing in manual production tasks. We show that demographic change is associated with greater adoption of robots and other automation technologies across countries and with more robotics-related activities across U.S. commuting zones. We also document more automation innovation in countries undergoing faster aging. Our directed technological change model predicts that the response of automation technologies to aging should be more pronounced in industries that rely more on middle-aged workers and those that present greater opportunities for automation and that productivity should improve and the labor share should decline relatively in industries that are more amenable to automation. The evidence supports all four of these predictions. 

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2. Modular Controllers Facilitate the Co-Optimization of Morphology and Control in Soft Robots

   https://doi.org/10.1145/3583131.3590416  

   Mertan, Alican; Cheney, Nick (July 2023, Proceedings of the Genetic and Evolutionary Computation Conference)

   Soft robotics is a rapidly growing area of robotics research that would benefit greatly from design automation, given the challenges of manually engineering complex, compliant, and generally non-intuitive robot body plans and behaviors. It has been suggested that a major hurdle currently limiting soft robot brain-body co-optimization is the fragile specialization between a robot's controller and the particular body plan it controls, resulting in premature convergence. Here we posit that modular controllers are more robust to changes to a robot's body plan. We demonstrate a decreased reduction in locomotion performance after morphological mutations to soft robots with modular controllers, relative to those with similar global controllers - leading to fitter offspring. Moreover, we show that the increased transferability of modular controllers to similar body plans enables more effective brain-body co-optimization of soft robots, resulting in an increased rate of positive morphological mutations and higher overall performance of evolved robots. We hope that this work helps provide specific methods to improve soft robot design automation in this particular setting, while also providing evidence to support our understanding of the challenges of brain-body co-optimization more generally. 

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3. Progress in robotics for combating infectious diseases

   https://doi.org/10.1126/scirobotics.abf1462  

   Gao, Anzhu; Murphy, Robin R.; Chen, Weidong; Dagnino, Giulio; Fischer, Peer; Gutierrez, Maximiliano G.; Kundrat, Dennis; Nelson, Bradley J.; Shamsudhin, Naveen; Su, Hao; et al (March 2021, Science Robotics)

   null (Ed.)

   The world was unprepared for the COVID-19 pandemic, and recovery is likely to be a long process. Robots have long been heralded to take on dangerous, dull, and dirty jobs, often in environments that are unsuitable for humans. Could robots be used to fight future pandemics? We review the fundamental requirements for robotics for infectious disease management and outline how robotic technologies can be used in different scenarios, including disease prevention and monitoring, clinical care, laboratory automation, logistics, and maintenance of socioeconomic activities. We also address some of the open challenges for developing advanced robots that are application oriented, reliable, safe, and rapidly deployable when needed. Last, we look at the ethical use of robots and call for globally sustained efforts in order for robots to be ready for future outbreaks. 

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4. Web Perspectives in Robotics Applications: Commonsense Knowledge, Autonomous Vehicles and Human-Robot Collaboration

   https://doi.org/10.1145/3583849.3583853  

   Conti, Christopher J.; Varde, Aparna S.; Wang, Weitian (March 2023, ACM SIGWEB Newsletter)

   The realms of commonsense knowledge and reasoning, vehicle automation with full as well as partial autonomy, and human-robot collaboration, present growing areas of research in recent times, with much of the concerned data being disseminated through the Web and devices encompassing IoT (Internet of Things); the data per se being heterogeneous including plain text, images, audiovisuals, hypertext and hypermedia. Due to the advent of autonomous vehicles, there is a greater need for the embodiment of commonsense knowledge within their development in order to simulate subtle, intuitive aspects of human judgment. The field of robotics has often encountered collaborative tasks between humans and robots to enhance the respective activities involved and produce better results than humans or robots would achieve working by themselves. Accordingly, this article outlines and organizes some of the research occurring in these areas along with its Web perspectives and applications. Context related to human-robot collaboration and commonsense knowledge appears via a survey of the literature. Vehicle automation is significant with the relevant studies: its definition and methods of improvement are of focus in the article. Some work in this area makes an impact on smart manufacturing. There is discussion on how human-robot collaboration is beneficial, and how commonsense knowledge is useful for the collaboration to occur in an enhanced manner. This article would be potentially interesting to various communities, e.g. AI professionals, Web developers, robotics engineers, and data scientists. 

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5. Connecting the Dots of Social Robot Design From Interviews With Robot Creators

   https://doi.org/10.3389/frobt.2022.720799  

   Alves-Oliveira, Patrícia; Orr, Alaina; Björling, Elin A.; Cakmak, Maya (June 2022, Frontiers in Robotics and AI)

   Despite promises about the near-term potential of social robots to share our daily lives, they remain unable to form autonomous, lasting, and engaging relationships with humans. Many companies are deploying social robots into the consumer and commercial market; however, both the companies and their products are relatively short lived for many reasons. For example, current social robots succeed in interacting with humans only within controlled environments, such as research labs, and for short time periods since longer interactions tend to provoke user disengagement. We interviewed 13 roboticists from robot manufacturing companies and research labs to delve deeper into the design process for social robots and unearth the many challenges robot creators face. Our research questions were: 1) What are the different design processes for creating social robots? 2) How are users involved in the design of social robots? 3) How are teams of robot creators constituted? Our qualitative investigation showed that varied design practices are applied when creating social robots but no consensus exists about an optimal or standard one. Results revealed that users have different degrees of involvement in the robot creation process, from no involvement to being a central part of robot development. Results also uncovered the need for multidisciplinary and international teams to work together to create robots. Drawing upon these insights, we identified implications for the field of Human-Robot Interaction that can shape the creation of best practices for social robot design. 

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