Robotics Research Research Articles

Understanding Social Robots: Attribution of Intentional Agency to Artificial and Biological Bodies.

Much research in robotic artificial intelligence (AI) and Artificial Life has focused on autonomous agents as an embodied and situated approach to AI. Such systems are commonly viewed as overcoming many of the philosophical problems associated with traditional computationalist AI and cognitive science, such as the grounding problem (Harnad) or the lack of intentionality (Searle), because they have the physical and sensorimotor grounding that traditional AI was argued to lack. Robot lawn mowers and self-driving cars, for example, more or less reliably avoid obstacles, approach charging stations, and so on-and therefore might be considered to have some form of artificial intentionality or intentional directedness. It should be noted, though, that the fact that robots share physical environments with people does not necessarily mean that they are situated in the same perceptual and social world as humans. For people encountering socially interactive systems, such as social robots or automated vehicles, this poses the nontrivial challenge to interpret them as intentional agents to understand and anticipate their behavior but also to keep in mind that the intentionality of artificial bodies is fundamentally different from their natural counterparts. This requires, on one hand, a "suspension of disbelief " but, on the other hand, also a capacity for the "suspension of belief." This dual nature of (attributed) artificial intentionality has been addressed only rather superficially in embodied AI and social robotics research. It is therefore argued that Bourgine and Varela's notion of Artificial Life as the practice of autonomous systems needs to be complemented with a practice of socially interactive autonomous systems, guided by a better understanding of the differences between artificial and biological bodies and their implications in the context of social interactions between people and technology.

Path Planning Algorithm Based on Obstacle Clustering Analysis and Graph Search

Path planning is receiving considerable interest in mobile robot research; however, a large number of redundant nodes are typically encountered in the path search process for large-scale maps, resulting in decreased algorithmic efficiency. To address this problem, this paper proposes a graph search path planning algorithm that is based on map preprocessing for creating a weighted graph in the map, thus obtaining a structured search framework. In addition, the reductions in the DBSCAN algorithm were analyzed. Subsequently, the optimal combination of the minPts and Eps required to achieve an efficient and accurate clustering of obstacle communities was determined. The effective edge points were then found by performing obstacle collision detection between special grid nodes. A straight-line connection or A* planning strategy was used between the effective edge points to establish a weighted, undirected graph that contained the start and end points, thereby achieving a structured search framework. This approach reduces the impact of map scale on the time cost of the algorithm and improves the efficiency of path planning. The results of the simulation experiments indicate that the number of nodes to be calculated in the search process of the weighted graph decreases significantly when using the proposed algorithm, thus improving the path planning efficiency. The proposed algorithm offers excellent performance for large-scale maps with few obstacles.

Global Navigation Satellite Systems as State-of-the-Art Solutions in Precision Agriculture: A Review of Studies Indexed in the Web of Science

Global Navigation Satellite Systems (GNSS) in precision agriculture (PA) represent a cornerstone for field mapping, machinery guidance, and variable rate technology. However, recent improvements in GNSS components (GPS, GLONASS, Galileo, and BeiDou) and novel remote sensing and computer processing-based solutions in PA have not been comprehensively analyzed in scientific reviews. Therefore, this study aims to explore novelties in GNSS components with an interest in PA based on the analysis of scientific papers indexed in the Web of Science Core Collection (WoSCC). The novel solutions in PA using GNSS were determined and ranked based on the citation topic micro criteria in the WoSCC. The most represented citation topics micro based on remote sensing were “NDVI”, “LiDAR”, “Harvesting robot”, and “Unmanned aerial vehicles” while the computer processing-based novelties included “Geostatistics”, “Precise point positioning”, “Simultaneous localization and mapping”, “Internet of things”, and “Deep learning”. Precise point positioning, simultaneous localization and mapping, and geostatistics were the topics that most directly relied on GNSS in 93.6%, 60.0%, and 44.7% of the studies indexed in the WoSCC, respectively. Meanwhile, harvesting robot research has grown rapidly in the past few years and includes several state-of-the-art sensors, which can be expected to improve further in the near future.

Research on Perception and Control Technology for Dexterous Robot Operation

Robotic grasping in cluttered environments is a fundamental and challenging task in robotics research. The ability to autonomously grasp objects in cluttered scenes is crucial for robots to perform complex tasks in real-world scenarios. Conventional grasping is based on the known object model in a structured environment, but the adaptability of unknown objects and complicated situations is constrained. In this paper, we present a robotic grasp architecture of attention-based deep reinforcement learning. To prevent the loss of local information, the prominent characteristics of input images are automatically extracted using a full convolutional network. In contrast to previous model-based and data-driven methods, the reward is remodeled in an effort to address the sparse rewards. The experimental results show that our method can double the learning speed in grasping a series of randomly placed objects. In real-word experiments, the grasping success rate of the robot platform reaches 90.4%, which outperforms several baselines.

Robotic surgery in obstetrics and gynecology: a bibliometric study.

We aimed to identify the trends and patterns of robotic surgery research in obstetrics and gynecology since its implementation. We used data from Clarivate's Web of Science platform to identify all articles published on robotic surgery in obstetrics and gynecology. A total of 838 publications were included in the analysis. Of these, 485 (57.9%) were from North America and 281 (26.0%) from Europe. 788 (94.0%) articles originated in high-income countries and none from low-income countries. The number of publications per year reached a peak of 69 articles in 2014. The subject of 344 (41.1%) of articles was gynecologic oncology, followed by benign gynecology (n = 176, 21.0%) and urogynecology (n = 156, 18.6%). Articles discussing gynecologic oncology had lower representation in low- and middle-income countries (LMIC) (32.0% vs. 41.6%, p < 0.001) compared with high income countries. After 2015 there has been a higher representation of publications from Asia (19.7% vs. 7.7%) and from LMIC (8.4% vs. 2.6%), compared to the preceding years. In a multivariable regression analysis, journal's impact factor [aOR 95% CI 1.30 (1.16-1.41)], gynecologic oncology subject [aOR 95% CI 1.73 (1.06-2.81)] and randomized controlled trials [aOR 95% CI 3.67 (1.47-9.16)] were associated with higher number of citations per year. In conclusion, robotic surgery research in obstetrics & gynecology is dominated by research in gynecologic oncology and reached a peak nearly a decade ago. The disparity in the quantity and quality of robotic research between high income countries and LMIC raises concerns regarding the access of the latter to high quality healthcare resources such as robotic surgery.

Actuation of Mobile Microbots: A Review

Maturation of robotics research and advances in the miniaturization of machines have contributed to the development of microbots and enabled new technological possibilities and applications. Microbots have a wide range of applications, including the navigation of confined spaces, environmental monitoring, micro‐assembly and manipulation of small objects, and in vivo micro‐surgeries and drug delivery. Actuators are among the most critical components that define the performance of robots. A comprehensive review of the actuation mechanisms that have been employed in mobile microbots is provided, including piezoelectric, magnetic, electrostatic, thermal, acoustic, biological, chemical, and optical actuation, with a focus on the most recent development and methodologies.

Research on the Frontier and Prospect of Service Robots in the Tourism and Hospitality Industry Based on International Core Journals: A Review.

This paper used the mixed research method of bibliometric and content analysis to study 284 studies on service robots in the tourism and hospitality industry collected from the Web of Science database. Results show that research in this field started late, and that the COVID-19 pandemic has promoted the rapid growth of the number of research papers. The International Journal of Contemporary Hospitality Management has so far published the most number of papers. Numerous scholars from universities in different regions of the world have made significant contributions to the research of service robots, and academic collaborations are relatively common, but there are only very few high-yield authors. Empirical research has been widely favored by researchers, wherein online questionnaire and experimental methods have been frequently used. Multidisciplinary theories have also been cited in related articles, especially on the applications of psychological theories. The research fronts cover four branches focusing on service robots, consumers, human employees, and service environment, with all four parts largely overlapping in content. Finally, the paper discusses prospects for the future research agenda of service robots in the tourism and hospitality industry.

Application and Prospect of Wave Energy in Marine Robots

Marine robots are an important tool for developing and exploring the ocean, which can adapt and work in the harsh marine environment. However, energy supply is one of the important factors that limit the operational capabilities of marine robots, and obtaining energy from the marine environment is an important way to improve the operating time and scope of marine robots. Wave energy is the most widely distributed in the ocean, with high energy flow density and easy to develop renewable clean energy. Therefore, wave energy can be used to provide energy for marine robots. Wave energy provides the possibility to solve the problem between the basic endurance and limited energy of marine robots. This paper introduces wave energy, summarizes the application of wave energy in marine robots, and analyzes its development trend, so as to provide reference for energy research of marine robots.

Reporting Conflicts of Interest in Robotic Cardiothoracic Surgical Research—It Is Still Partly Cloudy

Reporting Conflicts of Interest in Robotic Cardiothoracic Surgical Research—It Is Still Partly Cloudy

Design, Topology Optimization, and Additive Manufacturing of a Pneumatically Actuated Lightweight Robot

Soft robotics research has rapidly incorporated Additive Manufacturing (AM) into its standard prototyping repertoire. While numerous publications have highlighted the suitability of AM for producing soft pneumatic actuators, fluidic components, and lightweight structures, their integration into an industry-like robotic arm has not yet been shown. Against this background, a pneumatically actuated robot was developed that incorporates additively manufactured soft structures into rigid articulated hinges that generally allow for integration into today’s industrial production lines. The development of the robot, including pneumatic soft rotary bellows and rotary vane actuators (RVAs), is summarized, and its functionality is proven. It was found that using AM can increase the structural stiffness of robot links to a significant degree as manufacturing-related constraints in topology optimization are largely eliminated. Moreover, it was found that multi-material polyjet printing of soft rotary bellows actuators allows for highly integrated designs that provide low leakage and friction. However, these soft rotary actuators are still inferior in terms of endurance and performance if compared to AM replicas of RVAs. Our work narrows the gap between soft robotics research and today’s industrial applications, may realign research directions, and may provide impulses for the industry towards soft robotics and AM.

Sequential sensor fusion-based W-DDPG gait controller of bipedal robots for adaptive slope walking

Walking is a critical topic to the research and development of humanoid robots. However, humanoid robots in action often encounter diverse terrain, which impedes their ability to walk. A slope is a major challenge for humanoid robots. To address this challenge, a gait control algorithm based on wavelet transform and Deep Deterministic Policy Gradient was proposed in this study to enable robots to correct gait parameters in real time through continuous self-learning. In the algorithm, the signals of the three-axis accelerometer and three-axis gyroscope measured by an inertial measurement unit are decomposed and analyzed through wavelet transform to improve the learning outcomes. Robots were trained to walk on slopes with various angles to verify the proposed algorithm, which was also used to optimize the gait parameters of the central pattern generator. The experimental results revealed that the proposed algorithm is superior and more stable than other advanced algorithms. The feasibility and practicality of this algorithm were also verified in the experiments.

The effect of anthropomorphic competence-warmth congruence of service robots on recommendation intention

Service robots are becoming more popular as artificial intelligence technology advances. Based on the theory of mind perception, this study divides the anthropomorphism of service robots into two dimensions (competence and warmth) and discusses its impact on consumer psychology from the perspective of dual matching. First, anthropomorphism of service robots has positive effect on consumers’ attachment to robots. Second, consumer attachment to service robots increased when anthropomorphic competence and warmth were congruent. Third, consumer attachment to service robots mediated the relationship between anthropomorphic competence and warmth (in)congruence of service robots and consumer recommendation intention. Fourth, consumer paradox mindset moderated the effect of anthropomorphic competence and warmth (in)congruence of service robots on consumer attachment to service robots. These research conclusions have made important theoretical contributions and practical guidance for the research of anthropomorphic service robots and consumer attitudes.

Studies advanced in chatbots based on deep learning

Chatbots have always been a hot research topic in the field of human-computer interaction research, which aims to build a conversational intelligent response model to simulate human dialogue. Thanks to the rapid development of natural language processing technology and the continuous accumulation of dialogue data, the research of chat robots have made remarkable progress, which has gradually been widely used in various fields such as e-commerce and smart home. According to different technical frameworks, existing chatbots are mainly divided into two types: retrieval chatbots and generative chatbots. As the primary means of implementing chatbots in the industry, retrieval chatbots have smooth responses and low computational resource consumption. In contrast, generative chatbots do not require a predefined knowledge base and can dynamically generate responses based on the dialogue content. In this paper, focusing on the above two types of frameworks, we introduce the latest research progress in the field of deep learning-based chatbots in detail, including the representative algorithms and corresponding pipelines. Second, we compare the performance of representative algorithms on different datasets. We also summarize the problems chatbot technology research faces and give an outlook on its future development trends.

Possibilities and ethical issues of entrusting nursing tasks to robots and artificial intelligence.

In recent years, research in robotics and artificial intelligence (AI) has made rapid progress. It is expected that robots and AI will play a part in the field of nursing and their role might broaden in the future. However, there are areas of nursing practice that cannot or should not be entrusted to robots and AI, because nursing is a highly humane practice, and therefore, there would, perhaps, be some practices that should not be replicated by robots or AI. Therefore, this paper focuses on several ethical concepts (advocacy, accountability, cooperation, and caring) that are considered important in nursing practice, and examines whether it is possible to implement these ethical concepts in robots and AI by analyzing the concepts and the current state of robotics and AI technology. Advocacy: Among the components of advocacy, safeguarding and apprising can be more easily implemented, while elements that require emotional communication with patients, such as valuing and mediating, are difficult to implement. Accountability: Robotic nurses with explainable AI have a certain level of accountability. However, the concept of explanation has problems of infinite regression and attribution of responsibility. Cooperation: If robot nurses are recognized as members of a community, they require the same cooperation as human nurses. Caring: More difficulties are expected in care-receiving than in caregiving. However, the concept of caring itself is ambiguous and should be explored further. Accordingly, our analysis suggests that, although some difficulties can be expected in each of these concepts, it cannot be said that it is impossible to implement them in robots and AI. However, even if it were possible to implement these functions in the future, further study is needed to determine whether such robots or AI should be used for nursing care. In such discussions, it will be necessary to involve not only ethicists and nurses but also an array of society members.

Emerging technology in agriculture: Opportunities and considerations for occupational safety and health researchers

Introduction: A variety of factors are driving the development of robotics and automation in the agriculture industry including the nature of work, workforce shortages, and a variety of economic, climatic, technologic, political, and social factors. While some new robotics and automated machines are available commercially, most are still being developed. This provides occupational safety and health researchers an unprecedented opportunity to mitigate risks and benefit the health and safety of agriculture workers. Method: The NIOSH Office of Agriculture Safety and Health (OASH) is working to better understand how the advancements in automation and robotics is affecting workers. OASH is coordinating with the NIOSH Center of Occupational Robotics Research (CORR) to help to increase the understanding of human/machine interactions; improve the ability to identify injuries and fatalities involving automation/ robotics; and provide guidance on working safely with automation/ robotics. OASH also joined a small team of academics and industry to organize the SAfety For Emerging Robotics and Autonomous aGriculture or (SAFER AG) Workshop to identify gaps in knowledge and research needs that connect to issues related to risks and regulations/standards, occupational safety research, and impacts on workforce and society. This workshop was sponsored by USDA NIFA. Practical Applications: Occupational safety and health experts need to engage and collaborate with developers of technology. It is also increasingly important for occupational safety and health researchers and practitioners to not only become familiar with existing manufacturing safety standards, but also the lengthy standards development process. Joining consensus standards groups to help shape new standards for emerging technologies may help to mitigate adverse worker impacts. NIOSH’s Office of Agriculture Safety and Health will continue to identify research gaps, support new research projects, education, outreach efforts and the development of best practices with our partners.

An Analysis Review: Optimal Trajectory for 6-DOF-based Intelligent Controller in Biomedical Application

With technological advancements and the development of robots have begun to be utilized in numerous sectors, including industrial, agricultural, and medical. Optimizing the path planning of robot manipulators is a fundamental aspect of robot research with promising future prospects. The precise robot manipulator tracks can enhance the efficacy of a variety of robot duties, such as workshop operations, crop harvesting, and medical procedures, among others. Trajectory planning for robot manipulators is one of the fundamental robot technologies, and manipulator trajectory accuracy can be enhanced by the design of their controllers. However, the majority of controllers devised up to this point were incapable of effectively resolving the nonlinearity and uncertainty issues of high-degree freedom manipulators in order to overcome these issues and enhance the track performance of high-degree freedom manipulators. Developing practical path-planning algorithms to efficiently complete robot functions in autonomous robotics is critical. In addition, designing a collision-free path in conjunction with the physical limitations of the robot is a very challenging challenge due to the complex environment surrounding the dynamics and kinetics of robots with different degrees of freedom (DoF) and/or multiple arms. The advantages and disadvantages of current robot motion planning methods, incompleteness, scalability, safety, stability, smoothness, accuracy, optimization, and efficiency are examined in this paper.

Working with service robots? A systematic literature review of hospitality employees’ perspectives

Taking a systematic literature review approach, this study examines research on service robot adoption from hospitality employees’ perspectives. The findings reveal the current status of service robot research on hospitality employees by summarizing publication channels, temporal distribution, classifications of publications, and countries of focus of existing studies. This study also identifies key theories and constructs applied in existing research. Building on these, a holistic conceptual model including key antecedents, mediators, outcomes, and moderators in terms of service robot adoption among hospitality employees is proposed. Furthermore, several key promising research directions have been identified and discussed in this study, which serve as important references for researchers interested in pursuing this topic.

Bibliometric analysis of robotic surgery research in breast cancer conducted between 2008 and 2022.

To carry out a bibliometric analysis of robotic surgery research in the field of breast cancer conducted between 2008 and 2022 and to evaluate the status and trends in the field. A systematic search was undertaken in the Web of Science (WoS) for published articles related to surgical robots and breast cancer. R and VOSviewer software were used to carry out a quantitative analysis to explore the trend of annual publication volume and the cooperative relationship between countries, institutions, authors, and keywords. A total of 177 publications were retrieved, 79.66% of which were published from 2016 to 2022, and most were conducted in the United States (US), China, and South Korea. Articles from the US had the most frequent international cooperation. A tally of institutional publications showed that Yonsei University (YONSEI UNIV; Korea) had produced the most publications. The author with the most published papers was Lee of YONSEI UNIV. The most accepted journal was the Asian Journal of Surgery. Keyword co-occurrence analysis showed that current research hotspots were mainly focused on nipple-conserving mastectomy and breast reconstruction, and breast-conserving and nipple-conserving mastectomy may be future research hotspots. The annual incidence of robotic surgery and breast cancer is gradually increasing. The predominant countries conducting research in this field include the US, China, and South Korea, and the institutions are mainly distributed in universities and hospitals. Nipple-conserving mastectomy and breast reconstruction may be the current research hotspots, and breast-conserving mastectomy and minimally invasive surgery may represent hot research areas in the future. These findings may help scholars who are committed to the application of surgical robots to breast cancer to better understand the current research status and trends.

Compact Waist Rehabilitation Robot Inspired by McKenzie Therapy: Design, Analysis and Validation

Aiming at solving the problems of low compliance and unsatisfactory therapeutic effect in most existing waist rehabilitation robots, this letter presents a compact waist rehabilitation robot (CWRR) for patients with low back pain (LBP). First, the CWRR with a rigid pose adjustment mechanism and a soft curvature adjustment mechanism is designed to adapt to the waist movement and adjust lumbar curvature. Then, the kinematic analysis was conducted using the closed-loop vector method and the phenomenological theory model. Finally, unit mechanism tests and a comprehensive prototype test were carried out to validate the rationality of the theoretical models and the adaptability and compliance of the CWRR. The CWRR adjusted the curvature angle within the range of 10–60 degrees with small errors. Under different pose and curvature conditions, the man-machine contact pressure was lower or slightly higher than the low-pressure regime threshold (10 kPa). Experimental results show that the CWRR possesses potential clinical applications for patients with LBP disease and can provide theoretical and technical reserves for the research and development of curvature-adjustment waist rehabilitation robots.

Challenges and Perspectives in Scientific Publication of Robotics as an Interdisciplinary Field of Study

Challenges and Perspectives in Scientific Publication of Robotics as an Interdisciplinary Field of Study