Light-based nonverbal signaling with passive demonstrations for mobile service robots

With emerging applications in robotics that have the potential to bring them into our daily lives, it is expected for them to not only operate in close proximity to humans but also interact with them as well. When operating in crowded, human-populated environments there are many communication challenges faced by robots due to variable levels of interactions (e.g. asking for help, giving information, or navigating near humans). A crucial factor for success in these interactions is a robot’s ability to express information about their intent, actions, and knowledge to co-located humans. Many of the robot platforms developed for service roles have non-anthropomorphic form factors in order to simplify and tailor them to their jobs. Due to a lack of anthropomorphic features, these types of robots primarily communicate using an on-screen display and/or spoken language. To overcome the limitation of not communicating as people do, we explore the viability of nonverbal light-based signals as a communication modality for mobile service robots. These types of signals have many benefits over existing modalities which they can either complement or replace when appropriate, such as having long-range visibility and persisting over time. We present a novel light-based signal control architecture implemented as a custom Robot Operating System (ROS) software package generalized to allow for various signal implementations. We implement our framework on a BWIBot, an autonomous mobile service robot created as part of the Building-Wide Intelligence Project, and evaluate its validity through a real-world user study on the scenario where a robot and human are traversing a shared corridor from opposite ends, and the potential conflict created when their paths meet. Our results demonstrate that exposing users to the robot’s use of an animated light signal only once prior to when it is information critical for the user is sufficient to disambiguate its meaning, and thus greatly enhances its utility in-situ, with no direct instruction or training to the user. These findings suggest a paradigm of passive demonstration of light-based signals in future applications.Computer Science

User-Friendly: Anthropomorphic Devices and Mechanical Behaviour in Japan

Anthropomorphic avatars and disembodied voices have become part of every day life in Japan. From animated characters that bow after you complete a transaction at an automated teller machine to the phe-nomenal proliferation of consumer goods bearing cute faces. There is a discernable growing tendency to anthropomorphize machines. These anthropomorphic devices stand in contrast with the somewhat automated nature of many human interactions. Particularly in the behavior required of employees that work in customer service roles, which calls to mind the demand that workers must often behave as machines from which the notion of a robot originates. Based on research conducted at the National Museum of Emerging Science and Innovation in Tokyo, examples not only of how friendliness can be mechanically produced but also of new devices being imbued with functions to demonstrate their friendliness are critically examined

Intuitive Instruction of Industrial Robots : A Knowledge-Based Approach

With more advanced manufacturing technologies, small and medium sized enterprises can compete with low-wage labor by providing customized and high quality products. For small production series, robotic systems can provide a cost-effective solution. However, for robots to be able to perform on par with human workers in manufacturing industries, they must become flexible and autonomous in their task execution and swift and easy to instruct. This will enable small businesses with short production series or highly customized products to use robot coworkers without consulting expert robot programmers. The objective of this thesis is to explore programming solutions that can reduce the programming effort of sensor-controlled robot tasks. The robot motions are expressed using constraints, and multiple of simple constrained motions can be combined into a robot skill. The skill can be stored in a knowledge base together with a semantic description, which enables reuse and reasoning. The main contributions of the thesis are 1) development of ontologies for knowledge about robot devices and skills, 2) a user interface that provides simple programming of dual-arm skills for non-experts and experts, 3) a programming interface for task descriptions in unstructured natural language in a user-specified vocabulary and 4) an implementation where low-level code is generated from the high-level descriptions. The resulting system greatly reduces the number of parameters exposed to the user, is simple to use for non-experts and reduces the programming time for experts by 80%. The representation is described on a semantic level, which means that the same skill can be used on different robot platforms. The research is presented in seven papers, the first describing the knowledge representation and the second the knowledge-based architecture that enables skill sharing between robots. The third paper presents the translation from high-level instructions to low-level code for force-controlled motions. The two following papers evaluate the simplified programming prototype for non-expert and expert users. The last two present how program statements are extracted from unstructured natural language descriptions

Why Do Humans Imagine Robots?

This project analyzes why people are intrigued by the thought of robots, and why they choose to create them in both reality and fiction. Numerous movies, literature, news articles, online journals, surveys, and interviews have been used in determining the answer

iRobot : conceptualising SERVBOT for humanoid social robots

Services are intangible in nature and, as a result, it is often difficult to measure the quality of the service. The service is usually delivered by a human to a human customer and the service literature shows SERVQUAL can be used to measure the quality of the service. However, the use of social robots during the pandemic is speeding up the process of employing social roots in frontline service settings. An extensive review of the literature shows there is a lack of an empirical model to assess the perceived service quality provided by a social robot. Furthermore, the social robot literature highlights key differences between human service and social robots. For example, scholars have highlighted the importance of entertainment and engagement in the adoption of social robots in the service industry. However, it is unclear whether the SERVQUAL dimensions are appropriate to measure social robots’ service quality. This master’s project will conceptualise the SERVBOT model to assess a social robot’s service quality. It identifies reliability, responsiveness, assurance, empathy, and entertainment as the five dimensions of SERVBOT. Further, the research will investigate how these five factors influence emotional and social engagement and intention to use the social robot in a concierge service setting. To conduct the research, a 2 x 1 (CONTROL vs SERVBOT) x (Concierge) between-subject experiment was undertaken and a total of 232 responses were collected for both stages. The results indicate that entertainment has a positive influence on emotional engagement when service is delivered by a human concierge. Further, assurance had a positive influence on social engagement when a human concierge provided the service. When a social robot concierge delivered the service, empathy and entertainment both influenced emotional engagement, and assurance and entertainment impacted social engagement favourably. For both CONTROL (human concierge) and SERVBOT (social robot concierge), emotional and social engagement had a significant influence on intentions to use. This study is the first to propose the SERVBOT model to measure social robots’ service quality. The model provides a theoretical underpinning on the key service quality dimensions of a social robot and gives scholars and managers a method to track the service quality of a social robot. The study also extends the literature by exploring the key factors that influence the use of social robots (i.e., emotional and social engagement)

Apocalypse in Anime: Shifting Boundaries of Human Technology Interface

Anime is the definitive postmodern genre through which to portray apocalyptic narratives as it provides an imaginative liminal site that transcends any specific culture and ethnicity, and through which global concerns can be investigated. The study of apocalypse in selected anime - Japanese animated film and television - is beneficial at the outset o f the 21st century when we are beset with catastrophes both ecological and technological that are recognizably manufactured by some degree of human involvement. This examination is pertinent to disciplines as diverse as communications, cultural theory, anthropology, film, cyborg studies, Asian studies, and English literature. The dystopian settings and destructive elements in apocalyptic anime can be used in diverse and complex ways to comment on characterresponsetoupheavalanddisaster. Bystimulatingdiscussionthrough exploration of anime narratives, this popular culture product offers a pervasive and rich vocabulary with which to consider our reactions to adversity. This thesis demonstrates how the study of apocalypse through anime narratives is relevant to a greater understanding of our own behavior in reaction to apocalyptic circumstances

Advances in Human-Robot Interaction

Rapid advances in the field of robotics have made it possible to use robots not just in industrial automation but also in entertainment, rehabilitation, and home service. Since robots will likely affect many aspects of human existence, fundamental questions of human-robot interaction must be formulated and, if at all possible, resolved. Some of these questions are addressed in this collection of papers by leading HRI researchers

개발 초기 단계에서의 소셜 AI 개인비서 평가 모델 개발

학위논문(박사) -- 서울대학교대학원 : 공과대학 산업공학과, 2022.2. 윤명환.This dissertation aims to propose a user evaluation model to evaluate social AI personal assistants in the early stage of product development. Due to the rapid development of personal devices, data generated from personal devices are increasing explosively, and various personal AI services and products using these data are being launched. However, compared to the interest in AI personal assistant products, its market is still immature. In this case, it is important to understand consumer expectations and perceptions deeply and develop a product that can satisfy them to spread the product and allow general consumers to easily accept the product promptly. Accordingly, this dissertation proposes and validates a user evaluation model that can be used in the early stage of product development. Prior to proposing this methodology, main characteristics of social AI personal assistants, the importance of user evaluation in the early stage of product development and the limitations of the existing user evaluation model were investigated in Chapter 2. Various technology acceptance models and evaluation models for social AI personal assistant products have been proposed, evaluation models that can be applied in the initial stage of product development were insufficient, however. Moreover, it was found that commonly used evaluation measures for assessment of hedonic value were much fewer compared to measures for utilitarian value. These were used as starting points of this dissertation. In Chapter 3, the evaluation measures used in previous studies related to social AI personal assistant were collected and carefully reviewed. Through systematic review of 40 studies, the evaluation measures used in the past and limitation of related research were investigated. As a result, it was found that it was not easy to develop a prototype for evaluation, so it was possible to make the most of the products that have already been commercialized. In addition, all evaluation items used in previous studies were collected and used as the basis for the evaluation model to be proposed later. As a result of the analysis, considering the purpose of the social AI personal assistant, the role as supporting the user emotionally through social interaction with the user is important, but it was found that the evaluation measures related to hedonic value that are commonly used were still insufficient. In Chapter 4, evaluation measures that can be used in the initial stage of product development for social AI personal assistant were selected. Selected evaluation measures were used to evaluate three types of social robots and relationship among evaluation factors were induced through this evaluation. A process was proposed to understand to various opinions related to social robots and to derive evaluation items, and a case study was conducted in which a total of 230 people evaluated three social robots concept images using the evaluation items finally selected through this process. As a result, it is shown that consumers’ attitude toward products was built through the utilitarian dimension and the hedonic dimension. In addition, there is positive relationship between ease of use and utility in the utilitarian dimension, and among aesthetic pleasure, attractiveness of personality, affective value in the hedonic dimension. Moreover, it is confirmed that the evaluation model derived from this study showed superior explanatory power compared to the previously proposed technology acceptance model. In Chapter 5, the model was validated again by applying the evaluation measure and the relationship among evaluation factors derived in Chapter 4 to other products. 100 UX experts with expertise in the field of social AI personal assistants and 100 users who use the voice assistant service often, watched two concept videos of the voice assistant service to help users in the onboarding situation of mobile phones and evaluated these concepts. As a result of the evaluation, there is no significant difference in the evaluation results between the UX expert and the real user group, so the structural equation model analysis was conducted using all the data obtained from the UX expert and the real user group. As a result, results similar to those in Chapter 4 are obtained, and it is expected that the model could be generalized to social AI personal assistant products and applied for future research. This dissertation proposes evaluation measure and relationship among evaluation factors that can be applied when conducting user evaluation in the initial stage of social AI personal assistant development. In addition, case studies using social AI personal assistant products and services were conducted to validate it. With the findings of this study, it is expected that researchers who need to conduct user evaluation to clarify product concepts in the early stages of product development will be able to apply evaluation measures effectively. It is expected that the significance of this dissertation will become clearer if further research is conducted comparing the finished product of social AI personal assistants with the video type stimulus in the early stage of development.본 논문은 최근 빠르게 발전하고 있는 social AI personal assistant의 개발 초기 단계에 활용 가능한 사용자 평가 항목을 개발하고 평가 항목 간의 관계를 검증하는 것을 목표로 한다. 개인 디바이스의 발달로 인해, 각 디바이스에서 생성되는 데이터가 폭발적으로 증가하고 있고, 이를 활용한 개인용 AI 서비스 및 제품이 다양하게 제안되고 있다. 하지만 그 관심에 비해, social AI personal assistant 제품의 실제 시장은 아직 성숙하지 않은 단계이다. 이러한 상황에서 제품을 빠르게 확산시키고 일반 소비자들이 쉽게 제품을 수용할 수 있게 하기 위해서는, 소비자의 기대와 인식을 충분히 이해하고 그를 충족시킬 수 있는 제품을 개발하는 것이 중요하다. 이에 따라 본 연구에서는 제품 개발 초기 단계에 활용할 수 있는 사용자 평가 항목을 제안하고 평가 항목 간 관계를 도출하는 것을 목표로 한다. 먼저 2장에서는 social AI personal assistant의 특징, 제품 개발 초기 단계에서 이루어지는 사용자 평가의 중요성 및 기존 사용자 평가 모델의 한계점을 조사하였다. 기존에 기술 수용 모델 및 AI personal assistant 제품의 평가 모델들이 다양하게 제안되어 왔으나, 제품 개발 초기 단계에 활용할 수 있는 평가 모델은 부족하였고, 제품 전반을 평가할 수 있는 평가 모델의 부재로 대부분의 기존 연구에서는 두 가지 이상의 평가 모델을 결합, 수정하여 사용한 것을 알 수 있었다. 3장에서는 AI personal assistant 관련 기존 연구에서 활용된 평가 항목을 검토하였다. 총 40개의 연구를 리뷰하여, 기존에 활용되고 있는 평가 항목의 종류 및 한계점을 알아보았다. 그 결과, 평가를 위한 프로토타입 개발이 쉽지 않기에 이미 상용화된 제품들을 최대한 활용하는 것을 알 수 있었으며, 제품 전반을 평가한 사례는 부족함을 알 수 있었다. 또한 기존 연구들이 사용한 평가 항목을 모두 수집 및 정리하여 이후 제안할 평가 모델의 기반 자료로 활용하였다. 분석 결과, social AI personal assistant의 목적을 고려해보았을 때, 사용자와의 사회적 인터랙션을 통해 사용자의 감정적인 면을 채워주는 역할이 중요하지만, 공통적으로 활용하고 있는 감정적 가치 관련 평가 항목이 부족한 것으로 나타났다. 4장에서는 social AI personal assistant 제품 개발 초기 단계에서 활용 가능한 평가 항목을 수집 및 제안하고, 평가 항목을 활용하여 social robots을 평가한 뒤 이를 통해 평가 항목 간의 관계를 도출하였다. Social robots 관련 의견을 다양하게 청취하고 평가 항목을 도출하는 프로세스를 제안하였으며, 본 프로세스를 통해 최종 선정된 평가 항목을 이용하여, 총 230명이 세 가지 social robots 컨셉 영상을 평가하는 사례 연구를 진행하였다. 평가 결과, 제품에 대한 소비자 태도는 Utilitarian dimension과 Hedonic dimension을 통해 형성되었고, Utilitarian dimension 내 사용성 및 제품 효용성, Hedonic dimension에 포함되는 심미적 만족도, 성격의 매력도, 감성적 가치 각각은 서로 긍정적인 상관관계를 지님을 알 수 있었다. 또한 기존에 제안된 기술 수용 모델 대비 본 연구에서 도출한 평가 모델이 우수한 설명력을 보임을 확인하였다. 5장에서는 4장에서 도출된 평가 모델을 타 제품에 적용하여 모델을 다시 한번 검증하였다. 해당 분야에 전문성을 지닌 UX 전문가 100명 및 음성 비서 서비스를 실제 사용하는 실사용자 100명이, 휴대폰 온보딩 상황에서 사용자를 도와주는 음성 비서 서비스의 컨셉 영상 두 가지를 보고 컨셉에 대한 평가를 진행하였다. 평가 결과 UX 전문가와 실사용자 그룹 간에는 평가 결과에 유의미한 차이를 보이지 않았기 때문에, UX 전문가와 실사용자 그룹에서 얻은 데이터 전체를 활용하여 구조 방정식 모델 분석을 진행하였다. 그 결과 5장과 유사한 수준의 결과를 얻었고, 추후 해당 모델을 social AI personal assistant 제품에 일반화하여 활용할 수 있을 것으로 판단하였다. 본 논문은 social AI personal assistant 관련 제품 및 서비스의 개발 초기 단계에서 사용자 평가를 진행할 때 활용 가능한 평가 항목 및 평가 항목 간의 관계를 도출하였다. 또한 이를 검증하기 위하여 social AI personal assistant 제품 및 서비스를 활용한 사례연구를 진행하였다. 본 연구 결과는 추후 제품 개발 초기 단계에서 제품의 컨셉을 명확히 하기 위한 사용자 평가를 실시해야 하는 연구진이 효율적으로 활용할 수 있을 것으로 기대된다. 추후 이 부분의 검증을 위해, social AI personal assistants의 완제품과 개발 초기 단계의 video type stimulus를 비교하는 추가 연구가 이루어진다면 본 연구의 의미를 보다 명확하게 제시할 수 있을 것으로 생각된다.Chapter 1 Introduction 1 1.1 Background and motivation 1 1.1 Research objectives 5 1.2 Dissertation outline 7 Chapter 2 Literature review 9 2.1 Social AI personal assistant 9 2.2 User centered design process 13 2.3 Technology acceptance models 16 2.4 Evaluation measures for social AI personal assistant 22 2.5 Existing evaluation methodologies for social AI personal assistant 27 Chapter 3 Collection of existing evaluation measures for social AI personal assistants 40 3.1 Background 40 3.2 Methodology 43 3.3 Result 51 3.4 Discussion 60 Chapter 4 Development of an evaluation model for social AI personal assistants 63 4.1 Background 63 4.2 Methodology 66 4.2.1 Developing evaluation measures for social AI personal assistants 68 4.2.2 Conducting user evaluation for social robots 74 4.3 Result 77 4.3.1 Descriptive statistics 77 4.3.2 Hypothesis development and testing 80 4.3.3 Comparison with existing technology acceptance models 88 4.4 Discussion 93 Chapter 5 Verification of an evaluation model with voice assistant services 95 5.1 Background 95 5.2 Methodology 98 5.2.1 Design of evaluation questionnaires for voice assistant services 99 5.2.2 Validation of relationship among evaluation factors 103 5.3 Result 108 5.3.1 Descriptive statistics 108 5.3.2 Hypothesis development and testing 111 5.3.3 Comparison with existing technology acceptance models 118 5.4 Discussion 121 Chapter 6 Conclusion 124 6.1 Summary of this study 124 6.2 Contribution of this study 126 6.3 Limitation and future work 128 Bibliography 129 Appendix A. Evaluation measures for social AI personal assistant collected in Chapter 4 146 Appendix B. Questionnaires for evaluation of social robots 154 Appendix C. Questionnaires for evaluation of voice assistant service 166박

Discursive resources in the everyday construction of engineering knowledge /

Includes vita.Jaber F. Gubrium, Dissertation Supervisor.|Includes vita.Includes bibliographical references (pages 175-178)