Human-robot interaction: a conceptual framework for safety/risk analysis

Development of robotics and growing use of robots in many areas of the economy and social life require research which will identify problems related to the use of modern technologies and the development of human-robot interaction (HRI, Human-Robot Interaction). Robotics, autonomous systems and artificial intelligence also create a number of new legal and ethical challenges. Research in this area has been expanding in recent years, but there are still issues that require in-depth scientific exploration. The objective of this paper is to systematize knowledge about interactions between people and robots, with particular emphasis on interactions in the work environment, and to identify research gaps in the analysed problem area. The following research questions were formulated: 1) What determines people's attitudes towards robots? 2) What are the key challenges in human-robot communication? 3) What ethical challenges determine human-robot interaction? In the studies the the method of narrative literature review has been used. The latest scientific publications on the researched issue were analysed. The results of the study indicate that the main factors which determine people's attitudes towards robots are apart from demographic variables and experiences gained by people from contacts with robots, the perceived usefulness of using robots, the image of robots created in the mass media and religiousness. The key challenges in human-robot interaction apart from effective communication is the reflection of emotions. The research results enable the identification of further directions of scientific research on human-robot interaction. They can also enrich practitioner’s perspective in the studied area.

One of the challenges of outdoor robots is developing effective portable Human-Robot-Interaction (HRI) frameworks. Hand-held devices offer a practical solution. By equipping these devices with robot software, they can be made to interact with the outdoor robots. Android devices are ideal as they are open source and can be integrated with robots powered by the Robot Operating System (ROS), also open source. However, due to the limits of rosjava, the mechanism that links ROS with android, and the conflicting modes of operation between ROS and android, current implementations of ROS-android offer limited robot applications that do not support advanced operations such as autonomous navigation and others. This paper implements selective compartmentalization to overcome these limitations, by combining ROS with android through a number of ROS and android bridges that would facilitate the development of advanced robot applications. Through the proposed method, authors were able to develop a portable HRI framework that allowed human operators to supervise an outdoor mobile robot while it performed an autonomous task. From their mobile devices, users were able to initialize the robot, configure its motion, and monitor its progress. Also, users were able to reprogram the robot to perform new tasks (not previously planned) through a creative use of features offered in the developed HRI framework. Also, user cognitive effort was reported to be low as evident by the positive score on the NASA-TLX scale test which was corroborated with robot performance data. This paper presents the detailed development and implementation steps.

This article provides a comprehensive and comparative overview of the main types of robots, including social, educational, entertainment, industrial, collaborative, mobile, service, and humanoid robots, focusing on their technical, functional, and social characteristics. A key objective is to explore how anthropomorphic design, through human-like appearance, voice, and behavior, affects robot classification and shapes humanrobot interaction in different domains, including healthcare, education, retail, and entertainment. The study utilizes a structured literature review methodology that integrates recent peer-reviewed research in engineering, human-computer interaction, and the behavioral sciences. Through a comparative analysis, the paper identifies overarching topics such as the merging of technology capabilities, the increasing fluidity of robot classifications, and the ethical implications of emotional engagement with robots. Factors related to user trust, perceived agency, and consumer acceptance such as emotional intelligence, contextual adaptability, design aesthetics, and interaction intensity are examined. The results show that the increasing anthropomorphism of robots can significantly enhance user engagement, emotional attachment, and acceptance. However, it also raises important ethical challenges. These include the risks of emotional manipulation, stereotype reinforcement, and psychological dependence. The paper highlights that successful robot integration depends not only on technical efficiency, but also on ethical considerations, context-aware design, and the alignment of robot behavior with human social expectations. This paper provides original value by connecting technical classifications with socio-psychological dimensions of human-robot interaction, offering a conceptual framework for understanding how design elements and application context interact to influence societal acceptance.

Enhancing Humans Trust in Robots through Explanations

Towards establishing future-oriented relations between humans and robots, not only verbal, but also nonverbal robot functions have been studied. However, it is not clear how these different functions should be combined and implemented in robots in order to achieve ‘natural’ human-robot communication or interaction. In this paper, we focus on the timing for the coordination between utterance as a verbal function and body motion as a nonverbal function. To begin with, we investigated the temporal order and correlation between utterance and gesture in an interpersonal (human-human) interaction scenario as a preliminary experiment (Experiment 1). Then, we controlled the robot's response timing based on findings of the first experiment and evaluated the effectiveness of the robot's timing control in human-robot interaction (Experiment 2). It was shown that elderly participants significantly preferred the controlled robot's response. In addition, the timing of utterance and gestures affected the impression of the robot and interpretation of the verbal message. These results are important findings for designing socially interactive robots for the aging society.

Intelligent robotic systems will be found in several fields of everyday life in the near future. This implies an easy handling of an interaction with service robots by naive persons. Up till now many problems in human-robot interaction do exist; one of them is the great variety of human communication and behavior. Thus system designers often cannot anticipate human behavior which leads to frustrated users. We have devised a tool to analyze and code human and robot behavior during human-robot interaction, which can serve as a first stepping stone toward recognizing, automating coding and adapting robot behavior in order to obtain successful interactions. The tool called Interaction Analysis Protocol was used in different interaction scenarios between robot and human being. In this paper we present an experiment within which the robot acts as receptionist. The analysis and coded behaviors are based on the Interaction Analysis Protocol.

Actually, the research on human interactive robot (HIR) has been a topic of both science fiction and academic speculation for a long time. The origin of HIR as a discrete issue was stated by 20th century author Isaac Asimov in 1941, in his novel “I, Robot”. He stated the Three Laws of Robotics1 as, “ a. A robot may not injure a human being or, through inaction, allow a human being to come to harm. b. A robot must obey any orders given to it by human beings, except where such orders would conflict with the First Law. c. A robot must protect its own existence as long as such protection does not conflict with the First or Second Law. ” The three laws of robotics determine the idea of safe interaction which constitutes the basic rules of HIR. With the advances of artificial intelligence (AI), the HIR could eventually have more proactive behaviours, planning their motion in complex unknown environments. Nowadays, HIR are artificial agents with capacities of perception and action in the human’s environment. Their use has been tended to be found in the most technologically advanced societies in critical domains as search and rescue, military battle, law enforcement, entertainment, hospital care, etc. These domains of applications imply a closer interaction with human. The concept of closeness is to be taken in its full meaning, HIR and humans not only share the workspace but also share goals in terms of task achievement. The HIR has to adapt itself to human’s way of expressing desires and fulfill its task. Taking lifting up human in elder care for example, the human interactive robot RI-MAN, designed by the RIKEN Bio-Mimetic Control Research Center, communicates with human by listening and speaking, which makes it understand the human will (Onish, Luo et al. 2007). To fulfil the task, it also estimates the attitude of human body in real-time by tactile sense (Mukai, Onishi et al. 2008). This example contains two aspects of HIR, one is to understand the human mind and the other is to accomplish the manipulation. The former is based on AI techniques, like language comprehension, and the latter is relied on force control. On the other hand, human’s environments are much more complex. Thus, the HIR needs perceiving and understanding capacities to build dynamic models of its surroundings. It

Human–robot interaction (HRI), in all its different variants, has gained significant attention in industry. The combination of human skills and robotics significantly enhances manufacturing, improving operations quality and efficiency. This is particularly relevant in highly variable contexts like remanufacturing, which aims to preserve the value of products and components over time and involves complex, non-standardized tasks such as inspection, disassembly, reprocessing, and reassembly. Uncertainties related to the conditions of products to remanufacture cannot be managed by pure automation making HRI highly beneficial. Although researchers have focused on the use of HRI in several fields of application (from construction to logistics), no extensive mapping of the research trends has specifically addressed the intersection of HRI and remanufacturing contexts. To fill this gap, this paper presents a comprehensive study based on a bibliometric analysis to explore the current state of research on this topic. Based on 120 articles from the Scopus database, this study points out the main countries, authors, and affiliations involved in the field. In addition, the key topics were analyzed. A predominant focus, above all in the last three years, on Human-Robot Collaboration (HRC) among the different levels of HRI, and disassembly processes was highlighted, while other related activities, such as reassembly, have received comparatively less attention. An unexplored frontier is the integration of Artificial Intelligence and Machine Learning with HRC tasks in remanufacturing. These findings offer valuable insights for researchers, scholars, and industrial professionals aiming to advance HRI in remanufacturing.

The market for industrial robots grew rapidly during the 1970s and 1980s, with a peak demand in 1991. However, due to the subsequent recession in the world economy, the market for industrial robots has been slow or stagnant over the last decade. The value of industrial robots has decreased in that term, even though they have undergone considerable technical advances. On the other hand, human interactive robots for psychological enrichment are a type of service robots that provide a service by interacting with humans while stimulating their minds. As opposed to industrial robots, accuracy or speed is not always of prime importance. Their function or purpose is not simply entertainment, but also to render assistance, to guide, to provide therapy, to educate, to enable communication, and so on. The market for human interactive robots designed for psychological enrichment is expected to grow rapidly and to become more widespread. This overview explains human-robot interactions in terms of the relationship between humans and robots, in terms of the duration of these interactions and in terms of design issues affecting human interactive robots for psychological enrichment. Then examples of cross-cultural differences in the subjective evaluation of human interactive robots are described.

As robots become increasingly prevalent and capable, the complexity of roles and responsibilities assigned to them as well as our expectations for them will increase in kind. For these autonomous systems to operate safely and efficiently in human-populated environments, they will need to cooperate and coordinate with human teammates. Mental models provide a formal mechanism for achieving fluent and effective teamwork during human–robot interaction by enabling awareness between teammates and allowing for coordinated action. Much recent research in human–robot interaction has made use of standardized and formalized mental modeling techniques to great effect, allowing for a wider breadth of scenarios in which a robotic agent can act as an effective and trustworthy teammate. This paper provides a structured overview of mental model theory and methodology as applied to human–robot teaming. Also discussed are evaluation methods and metrics for various aspects of mental modeling during human–robot interaction, as well as recent emerging applications and open challenges in the field.

How Much Do Robots Understand Rudeness? Challenges in Human-Robot Interaction

This paper discusses how to align different kinds of ontologies: Japanese Wikipedia Ontology, Behavior Ontology and Robot Kinematics Ontology with built-in software, in order to design Multi-Level HRI (Human Robot Interaction). The multi-level interaction includes three-way interactions: knowledge-level interaction with dialog and fact type QA, behavior-level interaction between a user and a humanoid robot, and task-level interaction with multi robot coordination to do a task given from a user. Japanese Wikipedia Ontology works for language-level interaction, Behavior Ontology works for bridging the gaps between human behavior and robot one. Robot behavior goes well with Robot Kinematics. More complicated interaction can be done where three-way interactions invoke each other. Case studies show us that children in elementary school and elder persons enjoy the Multi-Level HRI.

In everyday applications of robotics, people will likely interact with groups of robots. Most human-robot interaction (HRI) research to date, however, has studied humans interacting with individual robots. Initial research suggests that humans respond differently to individual robots and robots in groups, making responses to groups of robots critical to study. This paper presents a study performed in a public setting familiar to participants (university cafeterias) to examine how participants respond when robots, individually and in groups, enter their space. We examined participant survey and behavioral responses to different numbers of robots (Single or Group) with different behaviors (Social or Functional). Because robots will be used across cultures, we performed the study in Japan and the USA. Across cultures, we found that people interact more with robots in groups than single robots, yet report similar levels of liking for both; participants also rated social robots as more friendly and helpful than functional robots in general. They rated single social robots more positively than a group of social robots, but a group of functional robots more positively than single functional robots. Japanese participants reported liking the robots more than USA participants. This suggests that researchers and designers should be aware of how robot characteristics influence group effects. Social human-robot interaction, group effects, robot behavior, cross-cultural study

Effective interactions between humans and robots are vital to achieving shared tasks in collaborative processes. Robots can utilize diverse communication channels to interact with humans, such as hearing, speech, sight, touch, and learning. Our focus, amidst the various means of interactions between humans and robots, is on three emerging frontiers that significantly impact the future directions of human–robot interaction (HRI): (i) human–robot collaboration inspired by human–human collaboration, (ii) brain-computer interfaces, and (iii) emotional intelligent perception. First, we explore advanced techniques for human–robot collaboration, covering a range of methods from compliance and performance-based approaches to synergistic and learning-based strategies, including learning from demonstration, active learning, and learning from complex tasks. Then, we examine innovative uses of brain-computer interfaces for enhancing HRI, with a focus on applications in rehabilitation, communication, brain state and emotion recognition. Finally, we investigate the emotional intelligence in robotics, focusing on translating human emotions to robots via facial expressions, body gestures, and eye-tracking for fluid, natural interactions. Recent developments in these emerging frontiers and their impact on HRI were detailed and discussed. We highlight contemporary trends and emerging advancements in the field. Ultimately, this paper underscores the necessity of a multimodal approach in developing systems capable of adaptive behavior and effective interaction between humans and robots, thus offering a thorough understanding of the diverse modalities essential for maximizing the potential of HRI.

Collaboration humans and robots in close proximity in a shared workspace is a stimulating feature of Industry 4.0. Collaborative robotics solution provides for the production processes the benefits due to the characteristic properties of robots. These properties include high level of accuracy, speed and repeatability. In combination with the flexibility and cognitive skills of humans the process of human-robot interaction achieves an efficient human-robot collaboration. Today’s topical issue research include problems of developing safer robots in human-machine systems. In considering the issue of safety human-robot interaction should be taken into account regulations and standards. A key challenge of human-robot collaboration is deciding how to distribute functions between human and robot to provide efficient interaction. This paper is a review on history of the robotic automation and modern research including Russian experience.