Volume 13, Issue 1

Background Social robots have been used in different roles, for example, in caregiving, companionship, and as a therapy tool, in recent years – with growing tendency. Although we still know little about factors that influence robots’ acceptance, studies have shown that robots are possible social companions for humans that help overcome loneliness, among other use cases. Especially in the given situation of forced social isolation, social companions are needed. This social gap might be filled by robots. We hypothesized that loneliness and the need to belong increase acceptance of social robots. Methods One hundred forty participants were asked to fill out an online survey on social robots and their acceptance in society. Questions on robots, demographical factors, and external factors (lockdown length) were asked and personal traits were also assessed. Results and interpretation As expected, among other findings, loneliness of participants was positively linked to robots’ acceptance. Nevertheless, need to belong was not. We conclude from these results that social robots are a possible social instrument to overcome loneliness and that interaction with a robot cannot replace belonging to a social group because robots lack needs that humans or animals have. Also, personality traits and demographic factors were linked to robots’ acceptance. This means that, even though there are generalizable connections between robots’ acceptance and factors as loneliness, personal traits are at least of similar importance. Discussion Our results provide important new insights into relationships between humans and robots and their limitations. Robots can ease our loneliness but are not seen as human. Future research needs to investigate factors that influence perception and acceptance of robots. Future lab-based studies with realistic human–robot interactions will deepen our insights of human understanding, perception, and acceptance of robots.

The inclusion of technologies such as telepractice, and virtual reality in the field of communication disorders has transformed the approach to providing healthcare. This research article proposes the employment of similar advanced technology – social robots, by providing a context and scenarios for potential implementation of social robots as supplements to stuttering intervention. The use of social robots has shown potential benefits for all the age group in the field of healthcare. However, such robots have not yet been leveraged to aid people with stuttering. We offer eight scenarios involving social robots that can be adapted for stuttering intervention with children and adults. The scenarios in this article were designed by human–robot interaction (HRI) and stuttering researchers and revised according to feedback from speech-language pathologists (SLPs). The scenarios specify extensive details that are amenable to clinical research. A general overview of stuttering, technologies used in stuttering therapy, and social robots in health care is provided as context for treatment scenarios supported by social robots. We propose that existing stuttering interventions can be enhanced by placing state-of-the-art social robots as tools in the hands of practitioners, caregivers, and clinical scientists.

Research has shown that people evaluate others according to specific categories. As this phenomenon seems to transfer from human–human to human–robot interactions, in the present study we focused on (1) the degree of prior knowledge about technology, in terms of theoretical background and technical education, and (2) intentionality attribution toward robots, as factors potentially modulating individuals’ tendency to perceive robots as social partners. Thus, we designed a study where we asked two samples of participants varying in their prior knowledge about technology to perform a ball-tossing game, before and after watching a video where the humanoid iCub robot was depicted either as an artificial system or as an intentional agent. Results showed that people were more prone to socially include the robot after observing iCub presented as an artificial system, regardless of their degree of prior knowledge about technology. Therefore, we suggest that the way the robot was presented, and not the prior knowledge about technology, is likely to modulate individuals’ tendency to perceive the robot as a social partner.

Across numerous disciplines, virtual reality (VR) had been used to aid decision-making in training, design, and evaluation processes. Both the educational and industrial groups have contributed to a vast knowledge based on a variety of VR topics during the last two decades. VR has been expanded to industry in recent years, but the majority of its applications do not involve industrial robots. To study the application of VR technology in industrial design, it is better to combine the design activities with computer-integrated manufacturing system and bring new opportunities for the innovation of industrial design. Therefore, in this article, an application of industrial interactive design system based on VR technology in the education domain is explored. First, the function and scheme design of industrial robot assembly and adjustment system are designed, and the model is established. Finally, SolidWorks and 3DsMAX are selected as three-dimensional model development tools. Unity 3D is used as the VR development engine; HTC VIVE is used as VR equipment. The study shows that the design of the machine motion instruction interpreter is effective, and the specific steps of the system to realize real-time control are also given. The feasibility of the system is verified through the analysis of typical applications of industrial robots.

A number of suggestions are made based on the improved evolutionary algorithm and using the polishing parameter optimization of an industrial robot as an example to optimize the industrial process parameter control. By fitting a cubic B-spline curve, the trajectory curve of each joint is determined. The kinematic constraint is replaced with the control point constraint of a B-spline curve, and the time optimal time node is solved using an enhanced evolutionary algorithm. This foundation allows for the creation of the nonlinear trajectory curve that satisfies the time optimization. The research shows that based on the improved genetic algorithm (GA), the “degradation” phenomenon of the traditional GA can be avoided, and the optimal solution can be obtained faster, that is, the polishing working time of the polishing industrial robot reaches the optimal level. An enhanced GA that incorporates simulated annealing is suggested to address the mathematical model of robot deburring process parameter optimization. Population selection is accomplished by the use of metropolis sampling, which successfully addresses the issue of the GA’s simple local convergence. The process parameter optimization verification is done while a robot deburring test platform is being constructed. The test results demonstrate a considerable reduction in burr removal time per unit length and an increase in efficiency when compared with the empirical method.

The high computational cost, complex external environment, and limited computing resources of embedded system are some major problems in traditional autonomous robot navigation methods. To overcome these problems, a mobile robot path planning navigation system based on panoramic vision was proposed. This method first describes the structure and functions of the navigation system. It explains how to use the environment to explore and map in order to create a panoramic vision sensor. Finally, it elaborates on the breadth-first search based on regression neural network (RNN) method, the Voronoi skeleton diagram method, the algorithm principle, and how to navigate by the planning path implementation of practical strategies. The simulation results illustrate that the breadth-first search method and the Voronoi skeleton graph method based on panoramic view have a high speed. The accessibility of RNN planning algorithm can effectively solve the difficult problems such as high computing overhead, complex navigation environment, and limited computing resources. In the actual robot navigation experiment, the difference in real-time performance and optimality performance that exists between the two algorithms is reflected in the length and duration of the course taken by the robot. When applied to a variety of site environments, the breadth-first search method requires between 23.2 and 45.3% more time to calculate the planned path than the Voronoi skeleton graph method, despite the fact that the planned path length is between 20.7 and 35.9% shorter using the breadth-first search method. It serves as a guide for choosing the appropriate algorithm to implement in practical applications.

Internet of Things (IoT) gadgets are very attractive globally, and IoT facilities are universal. Their progress has not been ignored, and the number of invaders and outbreaks on IoT and facilities is growing. Because cyber-assaults are zero-trust to the IoT, and the IoT is deeply ingrained in our lives and culture, we must embrace a comprehensive Zero-Trust strategy for cyber defense. As a result, the new model is no longer vulnerable to fear and outbreak on the IoT structure. In this article, an effort is made to categorize threat types and analyze and explain invaders and assaults on IoT gadgets and facilities.

Internet of medical things (IoMT) communication has become an increasingly important component of 5G wireless communication networks in healthcare as a result of the rapid proliferation of IoMT devices. Under current network architecture, widespread access to IoMT devices causes system overload and low energy efficiency. 5G-based IoMT systems aim to protect healthcare infrastructure and medical device functionality for longer. Therefore, using energy-efficient communication protocols is essential for enhancing QoS in IoMT systems. Several methods have been developed recently to improve IoMT QoS; however, clustering is more popular because it provides energy efficiency for medical applications. The primary drawback of the existing clustering technique is that their communication model does not take into account the chance of packet loss, which results in unreliable communication and drains the energy of medical nodes. In this study, we concentrated on designing a clustering model named Whale optimized weighted fuzzy-based cluster head selection algorithm to facilitate successful communication for IoMT-based systems. The experimental study shows that the proposed strategy performs better in terms of QoS than compared approaches. Inferring from this, the proposed method not only reduces energy consumption levels of 5G-based IoMT systems but also uniformly distributes cluster-head over a network to improve QoS.

Robots are rapidly growing technologies in simple words. Robots are artificial living things in this world that are created by humans for reducing human involvement in the top domains such as agriculture, medicine, and industries. Based on the requirements of work, robots are classified into six major categories. Robotic vehicles come under the division of autonomous mobile robots and automated guided vehicles. These vehicles are more popular in factories for supporting humans. Integration of artificial intelligence (AI) in a robotic vehicle gives the brain to the vehicle that can sense the surrounding environment and work accordingly without human operation. This article describes bibliometric research on the integration of AI in robotic vehicles. During the research, 1,196 documents are extracted from the Scopus database between 2015 till now. The types of publications included in this bibliometric analysis are articles, conference papers, reviews, book chapters, books, and short surveys that help understand the global research domain. The pictorial representation was made with the help of open-source platforms such as VOSviewer, GPS visualizer, Gephi, ScienceScape, and word cloud. This analysis helps understand the research gap in this domain.