Search results

This chapter aims to present the idea of leader robots (LRs) and proposes how LRs can step in to fill various manager positions. LRs are the robots that lead robots. Robotics engineers have already produced many robots for various applications such as in manufacturing, marketing, accounting even human resources in business management. We have witnessed many significant advancements in robotics and artificial intelligence research to achieve digital transformation. There are robots for various purposes of providing digital transformation toward Industry 5.0. Some post-modern organizations have already had robot employees and artificial intelligence applications. There are many studies on human–robot collaboration, robot development, and robot employee but limited research on LR. In this study, therefore, it is discussed the possibility of LRs that may be a key concept of Industry 5.0 in perspective digital transformation. Therefore, it is believed that this study will be one of the focuses of many upcoming organizational robotics research studies.

The purpose of this paper is to explore how robots are being used in libraries and information centers to transform their services and what are the future possibilities and trends in the application of robots in libraries.

Through a review of the literature, this paper analyzes various library websites and consults literature relating to the use of telepresence robots in libraries; the current application of robots in libraries has been enumerated along with case studies of libraries currently adopting telepresence robots.

With the practical examples of libraries using different types of robots, this study summarizes diverse activities of artificial intelligence-mediated robots. The uses of telepresence technology in libraries help to enhance library services, reach new users and provide a more inclusive and accessible library experience. Telepresence robots enhance the quality and accessibility of library services, expand library outreach and provide new opportunities for virtual engagement and programming. The application of telepresence robots in libraries can offer many benefits, but there are also several challenges that libraries must address to ensure successful implementation.

This study will motivate libraries and library professionals to take advantage of adopting telepresence robots in library and information center services and further accelerate library operations in the right direction.

This paper highlights how the introduction of telepresence robots in libraries improves services and productivity and creates a more engaging environment for the user group. The benefits and challenges of using robots in the library and the future trend in the application of telepresence robots in libraries are also discussed.

The main purpose of this paper is to explore telepresence robots are being used in libraries to facilitate library services and also to explain the future trend in the application of robots in libraries.

Through a review of the literature, this paper analyzes various library websites and consults literature relating to the use of telepresence robots in libraries; the current application of robots in libraries has been highlighted along with case studies of libraries currently adopting telepresence robots.

The uses of telepresence technology in libraries help to enhance library services, reach new users and provide a more inclusive and accessible library experience. Telepresence robots enhance the quality and accessibility of library services, expand library outreach and provide new opportunities for virtual engagement and programming. The application of telepresence robots in libraries can offer many benefits, but there are also several challenges that libraries must address to ensure successful implementation.

This paper highlights how the application of telepresence robots in libraries improves service productivity in libraries and creates a more engaging environment for the user group. The benefits and challenges of using robots in the library and the future trend in the application of telepresence robots in libraries are also discussed.

The purpose of this study is to solve the problems of poor stability and high energy consumption of the dynamic window algorithm (DWA) for the mobile robots, a novel enhanced dynamic window algorithm is proposed in this paper.

The novel algorithm takes the distance function as the weight of the target-oriented coefficient, and a new evaluation function is presented to optimize the azimuth angle.

The jitter of the mobile robot caused by the drastic change of angular velocity is reduced when the robot is closer to the target point. The simulation results show that the proposed algorithm effectively optimizes the stability of the mobile robot during operation with lower angular velocity dispersion and less energy consumption, but with a slightly higher running time than DWA.

A novel enhanced dynamic window algorithm is proposed and verified. According to the experimental result, the proposed algorithm can reduce the energy consumption of the robot and improves the efficiency of the robot.

The purpose of this paper is to propose a new velocity prediction navigation algorithm to develop a conflict-free path for robots in dynamic crowded environments. The algorithm BP-prediction and reciprocal velocity obstacle (PRVO) combines the BP neural network for velocity PRVO to accomplish dynamic collision avoidance.

This presented method exhibits innovation by anticipating ahead velocities using BP neural networks to reconstruct the velocity obstacle region; determining the optimized velocity corresponding to the robot’s scalable radius range from the error generated by the non-holonomic robot tracking the desired trajectory; and considering acceleration constraints, determining the set of multi-step reachable velocities of non-holonomic robot in the space of velocity variations.

The method is validated using three commonly used metrics of collision rate, travel time and average distance in a comparison between simulation experiments including multiple differential drive robots and physical experiments using the Turtkebot3 robot. The experimental results show that our method outperforms other RVO extension methods on the three metrics.

In this paper, the authors propose navigation algorithms capable of adaptively selecting the optimal speed for a multi-robot system to avoid robot collisions during dynamic crowded interactions.

Vision, audition, olfactory, tactile and taste are five important senses that human uses to interact with the real world. As facing more and more complex environments, a sensing system is essential for intelligent robots with various types of sensors. To mimic human-like abilities, sensors similar to human perception capabilities are indispensable. However, most research only concentrated on analyzing literature on single-modal sensors and their robotics application.

This study presents a systematic review of five bioinspired senses, especially considering a brief introduction of multimodal sensing applications and predicting current trends and future directions of this field, which may have continuous enlightenments.

This review shows that bioinspired sensors can enable robots to better understand the environment, and multiple sensor combinations can support the robot’s ability to behave intelligently.

The review starts with a brief survey of the biological sensing mechanisms of the five senses, which are followed by their bioinspired electronic counterparts. Their applications in the robots are then reviewed as another emphasis, covering the main application scopes of localization and navigation, objection identification, dexterous manipulation, compliant interaction and so on. Finally, the trends, difficulties and challenges of this research were discussed to help guide future research on intelligent robot sensors.

Limited by the types of sensors, the state information available for musculoskeletal robots with highly redundant, nonlinear muscles is often incomplete, which makes the control face a bottleneck problem. The aim of this paper is to design a method to improve the motion performance of musculoskeletal robots in partially observable scenarios, and to leverage the ontology knowledge to enhance the algorithm’s adaptability to musculoskeletal robots that have undergone changes.

A memory and attention-based reinforcement learning method is proposed for musculoskeletal robots with prior knowledge of muscle synergies. First, to deal with partially observed states available to musculoskeletal robots, a memory and attention-based network architecture is proposed for inferring more sufficient and intrinsic states. Second, inspired by muscle synergy hypothesis in neuroscience, prior knowledge of a musculoskeletal robot’s muscle synergies is embedded in network structure and reward shaping.

Based on systematic validation, it is found that the proposed method demonstrates superiority over the traditional twin delayed deep deterministic policy gradients (TD3) algorithm. A musculoskeletal robot with highly redundant, nonlinear muscles is adopted to implement goal-directed tasks. In the case of 21-dimensional states, the learning efficiency and accuracy are significantly improved compared with the traditional TD3 algorithm; in the case of 13-dimensional states without velocities and information from the end effector, the traditional TD3 is unable to complete the reaching tasks, while the proposed method breaks through this bottleneck problem.

In this paper, a novel memory and attention-based reinforcement learning method with prior knowledge of muscle synergies is proposed for musculoskeletal robots to deal with partially observable scenarios. Compared with the existing methods, the proposed method effectively improves the performance. Furthermore, this paper promotes the fusion of neuroscience and robotics.

Explore how the degree of humanization affects user misconduct, and provide effective misconduct prevention measures for the wide application of artificial intelligence in the future.

Based on the “Uncanny Valley theory”, three experiments were conducted to explore the relationship between the degree of humanization of service machines and user misbehavior, and to analyze the mediating role of cognitive resistance and the moderating role of social class.

There is a U-shaped relationship between the degree of humanization of service machines and user misbehavior; Social class not only regulates the main effect of anthropomorphism on misbehavior, but also regulates the intermediary effect of anthropomorphism on cognitive resistance, thus affecting misbehavior.

The design of the service robot can be from the user’s point of view, combined with the user’s social class, match different user types, and provide the same preferences as the user’s humanoid service robot.

This study is an important reference value for enterprises and governments to provide intelligent services in public places. It can prevent the robot from being vandalized and also provide users with a comfortable human-computer interaction experience, expanding the positive effects of providing smart services by government and enterprises.

This study avoids and reduces users' misbehavior towards intelligent service robots, improves users' satisfaction in using service robots, and avoids service robots being damaged, resulting in waste of government, enterprise and social resources.

From the perspective of product factors to identify the inducing factors of improper behavior, from the perspective of social class of users to analyze the moderating effect of humanization degree and user improper behavior.

The purpose of this research is to propose and empirically validate a theoretical framework to investigate the willingness of the elderly to disclose personal health information (PHI) to improve the operational efficiency of AI-integrated caregiver robots.

Drawing upon Privacy Calculus Theory (PCT) and the Technology Acceptance Model (TAM), 274 usable responses were collected through an online survey.

Empirical results reveal that trust, privacy concerns, and social isolation have a direct impact on the willingness to disclose PHI. Perceived ease of use (PEOU), perceived usefulness (PU), social isolation, and recognized benefits significantly influence user trust. Conversely, elderly individuals with pronounced privacy concerns are less inclined to disclose PHI when using AI-enabled caregiver robots.

Given the pressing need for AI-enabled caregiver robots due to the aging population and a decrease in professional human caregivers, understanding factors that influence the elderly's disclosure of PHI can guide design considerations and policymaking.

Considering the increased demand for accurate and comprehensive elder services, this is the first time that information disclosure and AI-enabled caregiver robot technologies have been combined in the field of healthcare management. This study bridges the gap between the necessity for technological improvement in caregiver robots and the importance of transparent operational information by disclosing the elderly's willingness to share PHI.

Within the scope of the research, articles about service robots were examined by the systematic review method.

The research aims to evaluate the articles on service robots, an artificial intelligence (AI) application in restaurant businesses, using a systematic review method. In systematic reviews, the data obtained as a result of scanning databases to find an answer to a research question are synthesized and reported. The criterion sampling technique, one of the purposeful sampling methods, was used for the sample of the research. Inclusion and exclusion criteria were applied within the scope of screening.

The articles on service robots were carried out between 2018 and 2023. In terms of research methods, most of the articles are quantitative, while there are studies on mixed and qualitative methods. In studies, data were generally collected by survey technique. The keywords of the studies on service robots are examined; the most commonly used words were service robot and AI, technology, restaurant, satisfaction, revisit intention, consumer behavior, intention, preference, hospitality and foods. The objectives of the articles pertinent to service robots are mostly to determine people's attitudes and acceptance toward these services focuses.

The studies seem to focus more on customer acceptance, trust, expectations, risks, adaptation, reasons for preference, impact on creative services, emotional and cognitive effects and human–robot interaction. Despite this, it is observed that there are fewer studies on topics such as the development of service robots in restaurant businesses, their reflections on the future, future opportunities and the quality of chef service robots. Based on this, it is recommended to consider studies that will serve as a reference for revealing innovative opportunities that can meet future expectations in order to increase the quality of service robots in restaurant businesses.