Robot Interaction Research Articles

An LLM-based vision and language cobot navigation approach for Human-centric Smart Manufacturing

Industry 5.0 prioritizes Human-centric Smart Manufacturing (HSM), aiming to enhance human operators’ well-being and needs. This necessitates collaborative robots with advanced natural interaction capabilities and improved perception, cognition, and action intelligence. The Large Language Model (LLM) exhibits strong reasoning abilities and generalization capabilities, which can significantly advance the development of HSM once integrated into human–robot interaction and collaboration. Accordingly, this paper explores part of LLM’s ability in the context of smart manufacturing, focusing on addressing interruptions in the manufacturing process caused by repetitive tool fetching. To alleviate this issue, a vision and language cobot navigation approach is innovatively adopted in the manufacturing environment that could be further used to assist operators in retrieving tools. Specifically, a real Human–Robot Collaboration (HRC) manufacturing scene is first reconstructed and annotated using Three-Dimensional (3D) point cloud techniques. Then the LLM is utilized for the Automated Guided Vehicle (AGV) to comprehend natural language commands and generate Python code to triger navigation actions. Finally, the Pathfinder algorithm is applied for corresponding path planning. The framework is implemented in the Artificial Intelligence (AI) Habitat simulator, and the case studies demonstrate that the AGV can accurately comprehend complex language instructions, empowering human operators to complete manufacturing tasks efficiently.

Are robots stealing our jobs? Examining robot-phobia as a job stressor in the hospitality workplace

Purpose The purpose of this study is to explore robot-phobia as a source of occupational stress among hospitality employees in the context of increasing robotization in the industry. Design/methodology/approach The study sampled 321 lodging employees and 308 food service employees in the USA. An online panel company recruited the participants and administered an online survey. The study used various analytical methods, including structural modeling, t-tests and multi-group analyses. Findings The study results reveal that hospitality workers experience robot-phobia regardless of their sector or position. Robot-phobia causes job insecurity and stress, which increases turnover intention. These negative outcomes are more pronounced for those who interact more frequently with robots. Practical implications The study findings suggest that hospitality workers fear being replaced by robots in the near future. Therefore, hospitality organizations should offer adequate training and education on the advantages and drawbacks of robots and establish a supportive and collaborative work environment that values human–robot interaction. Originality/value This study offers new insights regarding human–robot interaction from the employee perspective by introducing the concept of robot-phobia in the hospitality workplace. A comprehensive picture of how hospitality employees confront the increasing presence of robots is provided in this study.

Between Man and Machine: A Posthumanist Analysis of I, Robot

In Isaac Asimov’s groundbreaking anthology, I, Robot, the intricacies of human and robotic interactions take center stage, delving deep into questions of consciousness, right, morality. Characterized by Asimov’s unique blend of science fiction and philosophical pondering, the stories establish a framework to reflect on the evolving dynamics of an advanced technological society in space. Robots are capable to interact with human, to interpret complicate orders and act automatically, to help human with dull or dangerous works such as calculating and mining, even replacing the workers. Asimov also raised Three Laws of Robotics to make sure that all robots function in order. Through the lens of posthumanism, the anthology is examined for its portrayal of the blurred boundaries between human and artificial intelligences. Robots and human co-exist in the society. However, due to the limitation of “Three Laws of Robotics”, some logical contradictions inevitably appears and lead to the dysfunction of robots. As a result, I, Robot emerges as a poignant critique of humanity’s ethical and existential challenges in the face of rapid technological advancements. Building on existing research, this article attempts to forge a new perspective by reflecting on the broader implications of the artificial intelligence in Asimov’s works through the lens of post-humanism. It considers the existential questions of AI on a consciousness level, explores the egalitarian relationship between humans and machines from a rights perspective, and analyzes the concepts of “humanity” and “human-like” from a moral and ethical standpoint. It encourages readers to recognize that robots are not mere slaves to humans; instead, humans should view AI with equality and reverence towards the advancements of the era’s technology. Humanity should step away from anthropocentrism, not solely viewing humans as the measure of all things in this rapidly evolving era of AI, and properly handle the relationship between humans and non-humans. Currently, with rapid advancements in science and technology, the world of human-machine coexistence depicted by Isaac Asimov is increasingly becoming a reality. The emergence of artificial intelligences like AlphaGo and ChatGPT constantly reminds us of the advent of a post-human era. This article aims to examine the connections between AI and humans, discussing the dynamic interaction and mutual shaping between robots and human society. This article hopes to provide new thoughts and strategies for understanding and addressing the challenges brought by the age of artificial intelligence.

A framework for visual-based adaptive object-robot interaction of a mobile service robot

The COVID-19 pandemic (hereinafter “the pandemic”) necessitated social distancing measures and limited physical contact, prompting the exploration of alternative methods for tasks like object delivery. Mobile service robots emerged as a potential solution, offering a bridge between humans and various tasks. While existing techniques have been introduced to enable robots to deliver objects in an end-to-end manner, they come with limitations. Grippers, for instance, can deliver only one object per round, cabinet robots require manual speed tuning to keep the object in place, and object holders lack generalizability. Inspired by the idea of human nature to use a tray to deliver the object, we developed the Visual-Based Adaptive Interaction System (hereinafter “VAIS”), a novel learning system, to improve service delivery using visual information and a fast neural learning mechanism. Within this system, the robot learns the optimal angular rotational and linear translational moving speeds to effectively transport objects placed on a tray without an extra holder. The robot validates these learnt movements by successfully completing multiple-object delivery tasks along designated routes. The results exhibit that the robot can utilize online learning after a few attempts to determine its proper moving speed and deliver different objects to a given location.

Formation Control of Multiple Autonomous Mobile Robots Using Turkish Natural Language Processing

People use natural language to express their thoughts and wishes. As robots reside in various human environments, such as homes, offices, and hospitals, the need for human–robot communication is increasing. One of the best ways to achieve this communication is the use of natural languages. Natural language processing (NLP) is the most important approach enabling robots to understand natural languages and improve human–robot interaction. Also, due to this need, the amount of research on NLP has increased considerably in recent years. In this study, commands were given to a multiple-mobile-robot system using the Turkish natural language, and the robots were required to fulfill these orders. Turkish is classified as an agglutinative language. In agglutinative languages, words combine different morphemes, each carrying a specific meaning, to create complex words. Turkish exhibits this characteristic by adding various suffixes to a root or base form to convey grammatical relationships, tense, aspect, mood, and other semantic nuances. Since the Turkish language has an agglutinative structure, it is very difficult to decode its sentence structure in a way that robots can understand. Parsing of a given command, path planning, path tracking, and formation control were carried out. In the path-planning phase, the A* algorithm was used to find the optimal path, and a PID controller was used to follow the generated path with minimum error. A leader–follower approach was used to control multiple robots. A platoon formation was chosen as the multi-robot formation. The proposed method was validated on a known map containing obstacles, demonstrating the system’s ability to navigate the robots to the desired locations while maintaining the specified formation. This study used Turtlebot3 robots within the Gazebo simulation environment, providing a controlled and replicable setting for comprehensive experimentation. The results affirm the feasibility and effectiveness of employing NLP techniques for the formation control of multiple mobile robots, offering a robust and effective method for further research and development on human–robot interaction.

Improving Speed Characteristics of High-Torque-Density Motors for Physical Human–Robot Interaction Using an Independent Three-Phase Winding Structure

Recently, due to the decrease in labor force, increase in labor costs, and the desire for improved quality of life, research on robots has been actively conducted to address these issues. However, it is currently difficult to find robots that physically interact with humans. The reason is that the actuators of robots do not have a high torque density on their own. To solve this problem, high-torque-density motors, such as proprioceptive actuators, are being researched. However, the torque density is still insufficient for physical interaction with humans, so a motor with higher torque density has been developed. However, high-torque-density motors have the disadvantage of lower speed characteristics due to increased Back EMF levels. Therefore, to address the deterioration of speed characteristics in the developed motor, we applied the independent three-phase winding structure to improve the speed characteristics. Consequently, through comparison with the Y-Connection and D-Connection, we propose the most suitable winding structure for high-torque-density motors intended for physical interaction with humans.

Understanding stakeholders’ intention to use construction robots: a fuzzy-set qualitative comparative analysis

User acceptance is crucial for successfully adopting robotic technologies in the architecture, engineering, and construction (AEC) sector. Previous studies have focused on domestic, service, and industrial robots, leaving the construction domain unexplored. In this study, we set out to empirically understand how various dimensions of technology, environment, robot, and user lead to AEC stakeholders’ intention to use construction robots. We apply the fuzzy-set qualitative comparative analysis approach to capture the complexity of human behavior and the interdependencies across dimensions. For the data collection, we sampled 216 cases in Switzerland, Germany, and Austria evaluating three scenarios of human–robot interaction. Our analysis identifies three distinct user profiles—the lifelike robot user, the utilitarian robot user, and the lifelike-utilitarian robot user. The results show that human–robot peering may be a fundamental solution to increase user acceptance. By testing the effect of user characteristics, we also discover a lifelike-utilitarian type of robot that is more appealing to female AEC stakeholders. The study contributes to the construction robotics literature by providing tailored design and implementation strategies. It points to future research avenues such as user experience and social factors for exploring the impact of robotics and artificial intelligence in AEC.

Promising directions for human-robot interactions defined by older adults.

Introduction: Older adults are engaging more and more with voice-based agent and social robot technologies, and roboticists are increasingly designing interactions for these systems with older adults in mind. Older adults are often not included in these design processes, yet there are many opportunities for older adults to collaborate with design teams to design future robot interactions and help guide directions for robot development. Methods: Through a year-long co-design project, we collaborated with 28 older adults to understand the key focus areas that older adults see promise in for older adult-robot interaction in their everyday lives and how they would like these interactions to be designed. This paper describes and explores the robot-interaction guidelines and future directions identified by older adults, specifically investigating the change and trajectory of these guidelines through the course of the co-design process from the initial interview to the design guideline generation session to the final interview. Results were analyzed through an adapted ethnographic decision tree modeling approach to understand older adults' decision making surrounding the various focus areas and guidelines for social robots. Results: Overall, over the course of the co-design process between the beginning and end, older adults developed a better understanding of the robot that translated to them being more certain of their attitudes of how they would like a robot to engage with them in their lives. Older adults were more accepting of transactional functions such as reminders and scheduling and less open to functions that would involve sharing sensitive information and tracking and/or monitoring of them, expressing concerns around surveillance. There was some promise in robot interactions for connecting with others, body signal monitoring, and emotional wellness, though older adults brought up concerns around autonomy, privacy, and naturalness of the interaction with a robot that need to be further explored. Discussion: This work provides guidance for future interaction development for robots that are being designed to interact with older adults and highlights areas that need to be further investigated with older adults to understand how best to design for user concerns.

Managing social-educational robotics for students with autism spectrum disorder through business model canvas and customer discovery.

Social-educational robotics, such as NAO humanoid robots with social, anthropomorphic, humanlike features, are tools for learning, education, and addressing developmental disorders (e.g., autism spectrum disorder or ASD) through social and collaborative robotic interactions and interventions. There are significant gaps at the intersection of social robotics and autism research dealing with how robotic technology helps ASD individuals with their social, emotional, and communication needs, and supports teachers who engage with ASD students. This research aims to (a) obtain new scientific knowledge on social-educational robotics by exploring the usage of social robots (especially humanoids) and robotic interventions with ASD students at high schools through an ASD student-teacher co-working with social robot-social robotic interactions triad framework; (b) utilize Business Model Canvas (BMC) methodology for robot design and curriculum development targeted at ASD students; and (c) connect interdisciplinary areas of consumer behavior research, social robotics, and human-robot interaction using customer discovery interviews for bridging the gap between academic research on social robotics on the one hand, and industry development and customers on the other. The customer discovery process in this research results in eight core research propositions delineating the contexts that enable a higher quality learning environment corresponding with ASD students' learning requirements through the use of social robots and preparing them for future learning and workforce environments.

Optimizing service encounters through mascot-like robot with a politeness strategy

Mascot-like service robots embody anthropomorphic features, fostering affinity, and cultural representation. It is unknown whether they have politeness strategies that are more effective compared to humanoid robots. Drawing on politeness, uncanny valley, and mind perception theories, this study investigates the interaction effect of service robot appearance types (humanoid and mascot-like) and politeness strategies on customers’ service encounter evaluation, as well as the psychological mechanisms and boundary conditions of this effect. The findings reveal the superiority of mascot-like robots over humanoid robots in positive politeness contexts; human identity threat mediated this effect. Sense of power plays a moderating role; specifically, mascot robots with positive politeness strategies are more appealing to customers with low sense of power. This research significantly contributes to our understanding of service robot appearance and communication within the framework of mind perception and politeness theories in human–robot interaction. Moreover, it offers valuable guidance for companies enhancing consumer experiences through service robots.

PATIENT MONITORING HUMANOID ROBOT FOR PANDEMIC SITUATIONS

Humanoid robots are a rapidly evolving field of research and development that aims to create robots with human- l ike characteristics and capabilities. These robots possess a wide range of applications, from assisting humans in various tasks to exploring environments that are hazardous or inaccessible to humans. The development of humanoid robot involves the integration of advanced technologies, including robotics, artificial intelligence, computer vision, and natural language processing. This abstract explores the key aspects of humanoid robots, including their design, locomotion, perception, cognition, and interaction capabilities. It discusses the challenges involved in creating humanoid robots that can navigate complex environments, recognize and manipulate objects, understand and respond to human speech and gestures, and exhibit social behaviours. The abstract also highlights the potential benefits and ethical considerations associated with humanoid robots, such as their role in healthcare, education, e n t e r t a i n m e n t , a n d d i s a s t e r r e s p o n s e . Furthermore, the abstract addresses ongoing research efforts and technological advancements in the field of humanoid robotics, including the development of more dexterous and agile robot improvements in human- robot interaction, and the integration of machine learning and deep learning techniques. It emphasizes the importance of interdisciplinary collaboration and the need for robust hardware and software solutions to overcome the challenges faced in creating humanoid robots. Keywords—ATmega8 microcontroller, DHT Sensors, Heart Beat Sensor,LCD.

Enhancing Robot Inclusivity in the Built Environment: A Digital Twin-Assisted Assessment of Design Guideline Compliance

Developing guidelines for designing robot-inclusive spaces has been challenging and resource-intensive, primarily relying on physical experiments and observations of robot interactions within the built environment. These conventional methods are often costly, time-consuming, and labour-intensive, demanding manual intervention. To address these limitations, this study explores the potential of using digital twins as a promising solution to offer detailed insights, reducing the dependence on physical experiments for studying robot-built environment interactions.Although the concept of digital twins is popular in many domains, the use of digital twins for this specific problem has not been explored yet. A novel methodology for assessing existing built environment guidelines by incorporating them as an architectural digital twin asset within robot simulation software is proposed in this regard. By analysing the digital interactions between robots and the architectural digital twin assets in simulations, the compatibility of the environment with robots is evaluated, ultimately contributing to enhancing these guidelines to be robot-inclusive. The ultimate goal is to create environments that are not only inclusive but also readily accessible to Autonomous Mobile Robots (AMRs). With this objective, the proposed methodology is tested on robots of different specifications to understand the robots’ interactions with different architectural digital twin environments and obstacles. The digital twin effectively demonstrates the capability of the proposed approach in assessing the robots’ suitability for deployment in the simulated environments. The gained insights contribute to improved comprehension and strengthen the existing design guidelines.

Dielectric Elastomer-Based Actuators: A Modeling and Control Review for Non-Experts

Soft robotics are attractive to researchers and developers due to their potential for biomimicry applications across a myriad of fields, including biomedicine (e.g., surgery), the film industry (e.g., animatronics), ecology (e.g., physical ‘animats’), human–robot interactions (e.g., social robots), and others. In contrast to their rigid counterparts, soft robotics offer obvious actuation benefits, including their many degrees of freedom in motion and their potential to mimic living organisms. Many material systems have been proposed and used for soft robotic applications, involving soft actuators, sensors, and generators. This review focuses on dielectric elastomer (DE)-based actuators, which are more general electro-active polymer (EAP) smart materials. EAP-based soft robots are very attractive for various reasons: (a) energy can be efficiently (and readily) stored in electrical form; (b) both power and information can be transferred rapidly via electrical phenomena; (c) computations using electronic means are readily available. Due to their potential and benefits, DE-based actuators are attractive to researchers and developers from multiple fields. This review aims to (1) provide non-experts with an “easy-to-follow” survey of the most important aspects and challenges to consider when implementing DE-based soft actuators, and (2) emphasize current solutions and challenges related to the materials, controls, and portability of DE-based soft-actuator systems. First, we start with some fundamental functions, applications, and configurations; then, we review the material models and their selection. After, we outline material limitations and challenges along with some thermo-mechano-chemical treatments to overcome some of those limitations. Finally, we outline some of the control schemes, including modern techniques, and suggest using rewritable hardware for faster and more adaptive controls.

Ultra-Range Gesture Recognition using a web-camera in Human–Robot Interaction

Hand gestures play a significant role in human interactions where non-verbal intentions, thoughts and commands are conveyed. In Human–Robot Interaction (HRI), hand gestures offer a similar and efficient medium for conveying clear and rapid directives to a robotic agent. However, state-of-the-art vision-based methods for gesture recognition have been shown to be effective only up to a user-camera distance of seven meters. Such a short distance range limits practical HRI with, for example, service robots, search and rescue robots and drones. In this work, we address the Ultra-Range Gesture Recognition (URGR) problem by aiming for a recognition distance of up to 25 m and in the context of HRI. We propose the URGR framework, a novel deep-learning, using solely a simple RGB camera. Gesture inference is based on a single image. First, a novel super-resolution model termed High-Quality Network (HQ-Net) uses a set of self-attention and convolutional layers to enhance the low-resolution image of the user. Then, we propose a novel URGR classifier termed Graph Vision Transformer (GViT ) which takes the enhanced image as input. GViT combines the benefits of a Graph Convolutional Network (GCN) and a modified Vision Transformer (ViT). Evaluation of the proposed framework over diverse test data yields a high recognition rate of 98.1%. The framework has also exhibited superior performance compared to human recognition in ultra-range distances. With the framework, we analyze and demonstrate the performance of an autonomous quadruped robot directed by human gestures in complex ultra-range indoor and outdoor environments, acquiring 96% recognition rate on average.

Soft Robot Design, Manufacturing, and Operation Challenges: A Review

Advancements in smart manufacturing have embraced the adoption of soft robots for improved productivity, flexibility, and automation as well as safety in smart factories. Hence, soft robotics is seeing a significant surge in popularity by garnering considerable attention from researchers and practitioners. Bionic soft robots, which are composed of compliant materials like silicones, offer compelling solutions to manipulating delicate objects, operating in unstructured environments, and facilitating safe human–robot interactions. However, despite their numerous advantages, there are some fundamental challenges to overcome, which particularly concern motion precision and stiffness compliance in performing physical tasks that involve external forces. In this regard, enhancing the operation performance of soft robots necessitates intricate, complex structural designs, compliant multifunctional materials, and proper manufacturing methods. The objective of this literature review is to chronicle a comprehensive overview of soft robot design, manufacturing, and operation challenges in conjunction with recent advancements and future research directions for addressing these technical challenges.

Artificial intelligence in restaurant businesses: a systematic review on service robots

PurposeWithin the scope of the research, articles about service robots were examined by the systematic review method.Design/methodology/approachThe 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.FindingsThe 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.Originality/valueThe 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.

Robotic safety and hygiene attributes: visitors’ intention to receive robot-delivered hospitality services

Purpose This study aims to investigate tourists’ intentions to use hotel service robots with a focus on safety and hygiene. It examines the impact of perceived safety, health awareness and service assurance on consumer engagement and robot usage. Design/methodology/approach Survey data from 275 participants with experience in robotic service were analyzed using structural equation modeling (SEM). The study used purposive sampling and collected data via the Prolific platform, using SEM and SmartPLS Ver. 3.0 for analysis. Findings Results indicate customers prioritize safety and hygiene, valuing effective service responses and cleanliness. Perceived robotic safety and service assurance positively influence personal engagement, with a preference for service robots among female guests. Research limitations/implications While emphasizing the importance of safety and service assurance in hotel robotics, the study acknowledges limitations in personalization and conclusive use of service robots. Originality/value This research contributes to understanding the role of perceived safety in service robot usage, highlighting the significance of user trust and comfort in human–robot interactions. It also explores the novel connection between service assurance and service robots, offering insights into robotic performance reliability in user-centric contexts.

Implementations of Digital Transformation and Digital Twins: Exploring the Factory of the Future

In the era of rapid technological advancement and evolving industrial landscapes, embracing the concept of the factory of the future (FoF) is crucial for companies seeking to optimize efficiency, enhance productivity, and stay sustainable. This case study explores the concept of the FoF and its role in driving the energy transition and digital transformation within the automotive sector. By embracing advancements in technology and innovation, these factories aim to establish a smart, sustainable, inclusive, and resilient growth framework. The shift towards hybrid and electric vehicles necessitates significant adjustments in vehicle components and production processes. To achieve this, the adoption of lighter materials becomes imperative, and new technologies such as additive manufacturing (AM) and artificial intelligence (AI) are being adopted, facilitating enhanced efficiency and innovation within the factory environment. An important aspect of this paradigm involves the development and utilization of a modular, affordable, safe human–robot interaction and highly performant intelligent robot. The introduction of this intelligent robot aims to foster a higher degree of automation and efficiency through collaborative human–robot environments on the factory floor and production lines, specifically tailored to the automotive sector. By combining the strengths of human and robotic capabilities, the future factory aims to revolutionize manufacturing processes, ultimately driving the automotive industry towards a more sustainable and technologically advanced future. This study explores the implementation of automation and the initial strides toward transitioning from Industry 4.0 to 5.0, focusing on three recognized, large, and automotive companies operating in the north of Portugal.

Simulation research on interactive entertainment e-learning based on visual saliency testing in music multimedia teaching system

In traditional music teaching method, students passively accept information and lack sufficient interaction and participation. Entertainment robots can provide students with a more interesting and engaging learning experience through means such as multimedia content, gamified elements and interactive design. The goal of this research is to develop a technology based on visual saliency testing to improve the performance of entertainment robots in music teaching systems, making them more intelligent and interactive. The research collected a large number of music multimedia teaching materials, and marked and analyzed them. The visual significance test method is used to determine the key points and important information in the teaching materials, and the computer vision technology is used to identify the areas of visual interest to students in real time. Through interaction with students, the system can adapt its output based on student feedback to ensure personalized exploration and teaching of students' points of interest. Finally, an interactive entertainment robot system is designed, which can perform intelligent feedback and interaction according to the significant information in music teaching materials. The results show that the entertainment robot system based on visual salience test shows higher intelligence and interactivity in music multimedia teaching, which greatly improves the teaching experience.

A nuclear power plant digital twin for developing robot navigation and interaction

As robot technologies are rapidly improving, an increasing number of new ideas on utilizing robots for automated operation and maintenance tasks in nuclear power plants (NPPs) are being studied. However, due to safety concerns, researchers hardly found opportunities to test their new robot solutions on physical NPPs. In that sense, an efficient and realistic simulation environment plays a vital role in the development of automation systems for an NPP. In this paper, we propose the design of a 3D digital twin system capable of simulating NPP in real-time. This system obtains the data from a full-scope NPP simulator to reproduce the operating conditions of the plant. In addition, a scenario of a team of robots performing inspection tasks like temperature and pressure measurements will highlight its usability. This system enables development of intelligent robot swarms to deploy for inspection and maintenance purposes. It will positively impact autonomous control and operations for many types of reactors by reducing uncertainty in autonomous control and providing the tools necessary for remote intervention.