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At present, due to the COVID-19, China's social and economic development has slowed down. Some life service e-commerce platforms have successively launched "contactless delivery" services, which can effectively curb the spread of the epidemic. Robot distribution is the current mainstream, but robots are different from people and need to have accurate program settings. Both path planning and obstacle avoidance are currently top issues. This requires the mobile robot to successfully arrive at the destination while minimizing the impact on the surrounding environment and pedestrians, and avoiding encroachment on the movement space of pedestrians. Therefore, the mobile robot needs to be able to actively avoid moving pedestrians in a dynamic environment, in addition to avoiding static obstacles, and safely and efficiently integrate into the pedestrian movement environment. In this paper, the path planning problem of unmanned delivery robot is studied, and the path of mobile robot in the crowd is determined by global planning and local planning, and the matlab simulation is used for verification. © The Authors. Published under a Creative Commons Attribution CC-BY 3.0 License.
ABSTRACT
Eliminating pathogen exposure is an important approach to control outbreaks of epidemics such as COVID-19 (coronavirus disease 2019). To deal with pathogenic environments, using disinfection robots is a practicable choice. This research formulates a 3D (three-dimensional) spatial disinfection strategy for a disinfection robot. First, a disinfection robot is designed with an extensible control framework for the integration of additional functions. The robot has eight degrees of freedom that can handle disinfection tasks in complex 3D environments where normal disinfection robots lack the capability to ensure complete disinfection. An ingenious clamping mechanism is designed to increase flexibility and adaptability. Secondly, a new coverage path planning algorithm targeted at the spraying area is used. This algorithm aims to achieve an optimal path via the rotating calipers algorithm after transformation between a 2D (two-dimensional) array and 3D space. Finally, the performance of the designed robot is tested through a series of simulations and experiments in various spaces that humans usually live in. The results demonstrate that the robot can effectively perform disinfection tasks both in computer simulation and in reality.
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In recent years, due to the impact of COVID-19, the market prospect of non-contact handling has improved and the development potential is huge. This paper designs an intelligent truck based on Azure Kinect, which can save manpower and improve efficiency, and greatly reduce the infection risk of medical staff and community workers. The target object is visually recognized by Azure Kinect to obtain the center of mass of the target, and the GPS and Kalman filter are used to achieve accurate positioning. The 4-DOF robot arm is selected to grasp and transport the target object, so as to complete the non-contact handling work. In this paper, different shapes of objects are tested. The experiment shows that the system can accurately complete the positioning function, and the accuracy rate is 95.56%. The target object recognition is combined with the depth information to determine the distance, and the spatial coordinates of the object centroid are obtained in real time. The accuracy rate can reach 94.48%, and the target objects of different shapes can be recognized. When the target object is grasped by the robot arm, it can be grasped accurately according to the depth information, and the grasping rate reaches 92.67%. © 2023, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.
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Past research has discovered that the shape design and interaction process design of AI robots, as well as the users' constant features, are the major factors that affect users' willingness to interact with AI robots. Currently, AI robots that play a vital part in the daily activities of our society are becoming increasingly prevalent, thus things about AI robots have gone from mythic to prosaic. But when and where people are more likely to adopt AI robots remains an important research topic. With the development of online technology and the long-term impact of COVID-19, there has been a recent trend in the lower frequency of socializing. To investigate whether a state of low socializing frequency is a robotic moment and whether it affects people's willingness to interact with AI robots, we conducted two-wave questionnaire surveys to collect data from 300 participants from 23 provinces in China. The results showed that the frequency of socializing had a significant negative correlation with the willingness to interact with the AI robots via the mediation role of social compensation. Furthermore, the relationship between social compensation and willingness to interact with the AI robots was demonstrated to be stronger, when participants had a lower anthropomorphic tendency. These findings have theoretical implications for the human-computer interaction literature and managerial implications for the robotics industry. (PsycInfo Database Record (c) 2023 APA, all rights reserved)
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The COVID-19 outbreak has been designated a pandemic and is spreading quickly around the world. The industries most impacted by COVID-19, which has proved a barrier to every major business, were the e-commerce businesses that use door-to-door delivery methods. It's critical to have an unmanned strategy that can be applied to diverse sites during this key time. Although the driverless vehicle is not a novel idea, problems can occur when these systems run into the uneven pavement or unexpected obstacles. The methods for ensuring the stability of the commodities delivered by autonomous robots are discussed in this research. This mechanism guards against product damage. Additionally, a motor that stabilizes a robot's product compartment uses a gyroscope sensor to detect angular rotation and axial movement and preserve the orientation of a quadrupedal leg. In order to conduct trials that mimic problems in the real world, rectify errors, and offer solutions, a prototype model of a robot's stability platform has been created. This type of technological advancement will aid us in future efforts to combat global catastrophes. © 2023 IEEE.
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With the upgrading and innovation of the logistics industry, the requirements for the level of transportation smart technologies continue to increase. The outbreak of the COVID-19 has further promoted the development of unmanned transportation machines. Aimed at the requirements of intelligent following and automatic obstacle avoidance of mobile robots in dynamic and complex environments, this paper uses machine vision to realize the visual perception function, and studies the real-time path planning of robots in complicated environment. And this paper proposes the Dijkstra-ant colony optimization (ACO) fusion algorithm, the environment model is established by the link viewable method, the Dijkstra algorithm plans the initial path. The introduction of immune operators improves the ant colony algorithm to optimize the initial path. Finally, the simulation experiment proves that the fusion algorithm has good reliability in a dynamic environment. © 2022 IEEE.
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With the development and progress of intelligent algorithms, more and more social robots are used to interfere with the information transmission and direction of international public opinion. This paper takes the agenda of COVID-19 in Twitter as the breakthrough point, and through the methods of web crawler, Twitter robot detection, data processing and analysis, aims at the agenda setting of social robots for China issues, that is, to carry out data visualization analysis for the stigmatized China image. Through case analysis, concrete and operable countermeasures for building the international communication system of China image were provided. © 2022 IEEE.
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The COVID-19 pandemic has led to a surge of interest in research work involving the development of robotic systems that reduce human-to-human interaction, as such a technology can greatly benefit healthcare industries in preventing the spread of highly infectious diseases. An indoor service robot is built and equipped with wheel odometry and a 2D LiDAR. However, the presence of the systematic odometry errors is evident during field testing. Hence, the possibility of minimizing systematic odometry errors is inspected using various methods of calculation, namely: UMBmark, Lee's and Jung's. The methods all use the Bidirectional Square Path test, performed together with ROS. It is found that Jung's method is the most appropriate method showing a 20.4% improvement compared to the uncalibrated dead reckoning accuracy. Moreover, it is found that the presence of slippage, a nonsystematic error, greatly affects the return position errors of the robot. Consequently, it is recommended to improve the design of the wheelbase to minimize the effects of nonsystematic errors. © 2022 IEEE.
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Aims: During the COVID-19 pandemic, care for the elderly in the community was greatly limited. Accordingly, the demand for alternative community care have increased to cope with changing situations. In this study, we tried to find out whether the companion robot improved mood state and related problem in depressive or isolated community dwelling elderly. Method(s): For 186 community dwelling elderly who have received social welfare service due to depression or social isolation, we provided companion robot that could support their daily living. The robot was equipped with special program that could recognize and respond to the participant's own emotion. It was part of behavioural activation techniques which is one of powerful treatment for depression. The self-report questionnaires were used to measure changes in cognitive function, depression, suicidality, loneliness, resilience and satisfaction of life. Outcomes were measured before using companion robot and after 3 months, and we compared them. Result(s): The elderly using companion robot for 3 months showed improved cognitive function, depression (p < .001), suicidality (p < .001), and loneliness (p = .033) in the self-report questionnaire. Resilience (p = .749) and satisfaction of life (p = .246) were also improved but not reached significance. Conclusion(s): These findings showed that the use of companion robot with emotional recognition coaching program could help improve depression, cognitive function, loneliness and suicidal ideation. In particular, this effect was also useful for those who were diagnosed with depression. Also if we can put more techniques of behavioural activation programs into robot, it could be useful in community care for depressive and isolated elderly.
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This book chapter provides an overview of Temi, an autonomous, video-oriented personal assistant robot which was deployed within the Centre for Independent Language Learning (CILL) at The Hong Kong Polytechnic University. The artificial intelligence robot was chosen principally because of its role as a Robot as a Service (RaaS). Such a service can deliver greater self-improvement and better learning strategies (e.g. Cohen, A. D. (2014). Strategies in learning and using a second language (2nd ed.). Routledge., Dörnyei et. al., 2015, Wenden, Learner strategies for learner autonomy, Prentice Hall, 1991, Yang, Frontiers in Psychology 12:600, 218–600, 218, 2021) as well as foster beneficial attitudes and skills towards the users' long-term language learning success. Through its cloud-based system, Temi offers users access to dynamic interactions and enhanced CILL services, during the COVID-19 pandemic. As a whole, it appears that the introduction of Temi has proven to be an effective strategy to augment learners' autonomy. It further allows administrators to rethink how CILL services are conducted during human resource shortages. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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An increase in interest in research projects which involves the design of robotic systems that minimizes interactions between humans has been caused by the COVID-19 outbreak, as such technology can greatly benefit healthcare industries in preventing the spread of highly infectious diseases. The utilization of remote-controlled robots in many different fields, especially in the medical field is becoming more and more necessary. However, mobile robots are susceptible to both systematic and nonsystematic errors that cause deviations in its trajectory. In view thereof, the researchers explored the possibility of minimizing the trajectory errors through speed calibration. The differential drive robot was navigated to finish a five-meter linear path of forward and backward motion. The test was conducted with a default linear speed of 0.5 m/s in which a high trajectory error was observed. Upon changing the speed of the robot, the same trajectory test was conducted at four additional different speeds, namely;0.25 m/s, 0.35 m/s, 0.65m/s and 0.75 m/s. With the gathered data, the researchers conducted a linear least-squares regression model using MATLAB wherein there is only one predictor variable (speed of the robot) and one response variable (deviation). Based on the results, the researchers concluded that the speed of 0.35 m/s is the optimal speed in which the trajectory error of the robot is minimal. The researchers recommend improving the design of the caster wheels to minimize the effects of nonsystematic errors. © 2022 IEEE.
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Research on consumers' trust toward interaction with Artificially Intelligent (AI) social robots in service delivery has gained much more interest due to the outbreak of COVID-19 pandemic. However, this topic has not been widely invesgiated in China. To provide a psychometrically sound instrument in diverse cultural contexts, this study was to validate a scale of Social Service Robot Interaction Trust (SSRIT) that measures consumers' trust toward interaction with AI social robots in service delivery in a Chinese sample of adults. The results showed that the Chinese version of the SSRIT was validated with reliability and validity, suggesting that the Chinese version of the SSRIT could be used as an effective tool to assess trust in AI social robots in service delivery within the Chinese context. The implications of the findings were also discussed. [ FROM AUTHOR] Copyright of International Journal of Human-Computer Interaction is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)
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In this paper we will present a case in which a robot therapy for children with autism was transferred from clinic to home conditions. The developed application enables the children to continue with the interventions in home conditions. This proved especially important in the COVID-19 pandemic. The application also allows monitoring of the child's activities, through which the therapist can later analyze the patient's behavior and offer appropriate therapy. The application shows reliable results and gives promise to develop beyond the user case we are considering. © 2023 IEEE.
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With the developments of medical artificial intelligence (AI), meta-data analysis, intelligence-aided drug design and discovery, surgical robots and image-navigated precision treatments, intelligent medicine (IM) as a new era evolved from ancient medicine and biomedical medicine, has become an emerging topic and important criteria for clinical applications. It is fully characterized by fundamental research-driven, new-generation technique-directed as well as state-of-the-art paradigms for advanced disease diagnosis and therapy leading to an even broader future of modern medicine. As a fundamental subject and also a practice-oriented field, intelligent medicine is highly trans-disciplinary and cross-developed, which has emerged the knowledge of modern medicine, basic sciences and engineering. Basically, intelligent medicine has three domains of intelligent biomaterials, intelligent devices and intelligent techniques. Intelligent biomaterials derive from traditional biomedical materials, and currently are endowed with multiple functionalities for medical uses. For example, micro-/nanorobots, smart responsive biomaterials and digital drugs are representative intelligent biomaterials which have been already commercialized and applied to clinical uses. Intelligent devices, such as surgical robots, rehabilitation robots and medical powered exoskeleton, are an important majority in the family of intelligent medicine. Intelligent biomaterials and intelligent devices are more and more closely integrated with each other especially on the occasions of intelligence acquisition, remote transmission, AI-aided analysis and management. In comparison, intelligent techniques are internalized in the former two domains and are playing a critical role in the development of intelligent medicine. Representative intelligent techniques of telemedicine, image-navigated surgery, virtual/augmented reality and AI-assisted image analysis for early-stage disease assessments have been employed in nowadays clinical operations which to a large extent relieved medical labors. In the past decades, China has been in the leading groups compared to international colleagues in the arena of intelligent medicine, and a series of eminent research has been clinically translated for practical uses in China. For instance, the first 5G-aided remote surgery has been realized in Fujian Province in January 2019, which for the first time validated their applicability for human uses. The surgical robots have found China as the most vigorous market, and more than 10 famous Chinese companies are developing versatile surgical robots for both Chinese people and people all over the world. China also applied AI techniques to new drug developments especially in early 2020 when COVID-19 epidemic roared, and several active molecules and drug motifs have been discovered for early-stage COVID-19 screening and treatments. Based on the significance of intelligent medicine and its rapid developments in both basic research and industrials, this review summarized the comprehensive viewpoints of the Y6 Xiangshan Science Conferences titled with Fundamental Principles and Key Technologies of Intelligent Medicine, and gave an in-depth discussion on main perspectives of future developments of the integration of biomaterial and devices, the integration of bioinformatics and medical hardware, and the synergy of biotechnology and intelligence information. It is expected that this featuring article will further promote intelligent medicine to an even broader community not only for scientists but also for industrials, and in the long run embrace a perspective future for its blooming and rich contributions in China in the coming 5 years.
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Companion bots such as chatbots in cyberspace or robots in real space gained popularity during the COVID-19 pandemic as a means of comforting humans and reducing their loneliness. These bots can also help enhance the lives of elderly people. In this paper, we present how to design and implement a quick prototype of companion bots for elderly people. A companion bot named "Hello Steve"that is able to send emails, open YouTube to provide entertainment, and remember the times an elderly person must take medicine and remind them is designed and implemented as a quick prototype. In addition, the bot combines the features of a mobile robot and a chatbot. The experimental results show the effectiveness of the design through its very high accuracy when navigating mobile-robot-like tasks and responding to chatbot-like tasks via voice commands. © 2023 MYU K.K.
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Through the last decade, and particularly after the Covid period (2020 - 2022), crowd counting and localization have attracted much attention of AI researchers due to its potential applicability in crowd monitoring and control, public safety, space design, interactive content delivery etc. Once delivery objectives for a system are envisaged and the premises are fixed, we can always construct manifold technology architecture that delivers the set goals. However, in the Indian context a solution of choice needs to be optimized on frugality and ease of adaptability. In this paper we report an economic and replicable application of crowd counting and interactive content delivery in museums through unbiased knowledge systems embedded in robotic museum assistants. We intend to demonstrate a robotic system that can deliver any gallery content to groups of visitors keeping special focus on the exhibits that are popular choices. Crowd counting is used here to enable the content presentation to a group of choice in an interactive way. There are some market-ready solutions available for interactive gallery demonstration by moveable robots but they require not only huge capital investment but are also of limited use within controlled environments. Our proposed design is to multiplex an existing infrastructure of surveillance system as a smart crowd counting and gallery demonstration system along with crowd management with minimum additional hardware infusion. © 2023 IEEE.
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In 2019, the Novel Coronavirus Disease (COVID-19) was categorized as a pandemic. This disease can be transmitted via droplets on items or surfaces within several hours. Therefore, the researchers aimed to develop a wirelessly controlled robot arm and platform capable of picking up objects detected via object detection. Robot arm movements are done via the use of inverse kinematics. Meanwhile, a custom object detection model that can detect objects of interest will be trained and implemented in this project. To achieve this, the researchers utilize various open-source libraries, microcontrollers, and readily available materials to construct and program the entire system. At the end of this research, the prototype could reliably detect objects of interest, along with a grab-and-dispose success rate of 88%. Instruction data can be properly sent and received, and dual web cam image transfer reaches up to 1.72 frames per second. © 2023 IEEE.
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A "Stroke" is a neurological disease due to poor blood flowing to the brain, resulting in body cell death. It is ranked second as the most common cause of death globally. The "World Health Organization" estimates that about 15 million people suffer a stroke annually. Most stroke survivors have gait disorders, and most patients cannot walk without assistance. Physiotherapy is crucial for stroke patients to recover and maintain their mobility, functionality, and well-being. In the last 20 years, the replacement of physiotherapists with wearable robotics has become essential due to the developing technology, the need for economic growth, and the challenging health circumstances around the world, such as the COVID-19 pandemic recently. Lower Limb Exoskeleton (LLE) represents the solution for stroke patients under such circumstances, though its performance is a critical challenge paid attention to in the industry. This challenge has motivated the researchers to investigate the application of gait rehabilitation. This review presents and discusses the developments in the control system of LLE over the last decade. It also explores the limitations, new directions, and recommendations in LLE development according to the literature.
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In recent years, the novel corona virus pandemic is raging around the world, and the safety of home environment and public environment has become the focus of people's attention [2]. Therefore, the research on disinfection robot has become one of the important directions in the field of machinery and artificial intelligence. This paper proposes a robot with the STM32 MCU as the core of disinfection, and is equipped with a variety of sensors and a camera vision, has the original cloud service management platform, the remote deployment of navigation, based on visual SLAM to realize high precision navigation and positioning, can realize to indoor environment autonomously route planning, automatic obstacle avoidance checking, disinfection, epidemic prevention function, at the same time can pass Bit computer software realizes remote control of robot, which has great development potential. © 2022 ACM.