Social and collaborative aspects of interaction with a service robot

To an increasing extent, robots are being designed to become a part of the lives of ordinary people. This calls for new models of the interaction between humans and robots, taking advantage of human social and communicative skills. Furthermore, human–robot relationships must be understood in the context of use of robots, and based on empirical studies of humans and robots in real settings. This paper discusses social aspects of interaction with a service robot, departing from our experiences of designing a fetch-and-carry robot for motion-impaired users in an office environment. We present the motivations behind the design of the Cero robot, especially its communication paradigm. Finally, we discuss experiences from a recent usage study, and research issues emerging from this work. A conclusion is that addressing only the primary user in service robotics is unsatisfactory, and that the focus should be on the setting, activities and social interactions of the group of people where the robot is to be used.     

Psychological Effects of Behavior Patterns of a Mobile Personal Robot

It is envisioned that in the near future personal mobile robots will be assisting people in their daily lives. An essential characteristic shaping the design of personal robots is the fact that they must be accepted by human users. This paper explores the interactions between humans and mobile personal robots, by focusing on the psychological effects of robot behavior patterns during task performance. These behaviors include the personal robot approaching a person, avoiding a person while passing, and performing non-interactive tasks in an environment populated with humans. The level of comfort the robot causes human subjects is analyzed according to the effects of robot speed, robot distance, and robot body design, as these parameters are varied in order to present a variety of behaviors to human subjects. The information gained from surveys taken by 40 human subjects can be used to obtain a better understanding of what characteristics make up personal robot behaviors that are most acceptable to the human users.     

Experimental investigation into influence of negative attitudes toward robots on human–robot interaction

Negative attitudes toward robots are considered as one of the psychological factors preventing humans from interacting with robots in the daily life. To verify their influence on humans‘ behaviors toward robots, we designed and executed experiments where subjects interacted with Robovie, which is being developed as a platform for research on the possibility of communication robots. This paper reports and discusses the results of these experiments on correlation between subjects’ negative attitudes and their behaviors toward robots. Moreover, it discusses influences of gender and experience of real robots on their negative attitudes and behaviors toward robots.

Exploring the design space of robots: Children''s perspectives

Children's perceptions and evaluations of different robot designs are an important unexplored area within robotics research considering that many robots are specifically designed for children. To examine children's feelings and attitudes towards robots, a large sample of children (N = 159) evaluated 40 robot images by completing a questionnaire for each image, which enquired about robot appearance, robot personality dimensions and robot emotions. Results showed that depending on a robot's appearance children clearly distinguished robots in terms of their intentions (i.e. friendly vs. unfriendly), their capability to understand, and their emotional expression. Results of a principal components analysis of the children's ratings of the robots' personality attributes revealed two dimensions labelled ‘Behavioural Intention’ and ‘Emotional Expression’. Robots were classified according to their scores on these two dimensions and a content analysis of their appearance was conducted in an attempt to identify salient features of different robot personalities. Children judged human-like robots as aggressive, but human–machine robots as friendly. Results on children's perceptions of the robots' behavioural intentions provided tentative empirical support for the Uncanny Valley, hypothesized by (Mori, M., 1970), reflecting a situation where robots are very human-like, but still distinguishable from humans, evoking a feeling of discomfort or repulsion. The paper concludes with a discussion of design implications for robots, and the use of robots in educational contexts.     

The influence of empathy in human–robot relations

The idea of robotic companions capable of establishing meaningful relationships with humans remains far from being accomplished. To achieve this, robots must interact with people in natural ways, employing social mechanisms that people use while interacting with each other. One such mechanism is empathy, often seen as the basis of social cooperation and prosocial behaviour. We argue that artificial companions capable of behaving in an empathic manner, which involves the capacity to recognise another's affect and respond appropriately, are more successful at establishing and maintaining a positive relationship with users. This paper presents a study where an autonomous robot with empathic capabilities acts as a social companion to two players in a chess game. The robot reacts to the moves played on the chessboard by displaying several facial expressions and verbal utterances, showing empathic behaviours towards one player and behaving neutrally towards the other. Quantitative and qualitative results of 31 participants indicate that users towards whom the robot behaved empathically perceived the robot as friendlier, which supports our hypothesis that empathy plays a key role in human–robot interaction.     

Estimation of physical interaction between a musculoskeletal robot and its surroundings

Recently, robots are expected to support our daily lives in real environments. In such environments, however, there are a lot of obstacles and the motion of the robot is affected by them. In this research, we develop a musculoskeletal robotic arm and a system identification method for coping with external forces while learning the dynamics of complicated situations, based on Gaussian process regression (GPR). The musculoskeletal robot has the ability to cope with external forces by utilizing a bio-inspired mechanism. GPR is an easy-to-implement method, but can handle complicated prediction tasks. The experimental results show that the behavior of the robot while interacting with its surroundings can be predicted by our method.     

Interactive Humanoid Robots for a Science Museum

One objective of the Intelligent Robotics and Communication Laboratories is to develop an intelligent communication robot that supports people in an open everyday environment by interacting with them. A humanoid robot can help achieve this objective because its physical structure lets it interact through human-like body movements such as shaking hands, greeting, and pointing. Both adults and children are more likely to understand such interactions than interactions with an electronic interface such as a touch panel or buttons. To behave intelligently during an interaction, a robot requires many types of information about its environment and the people with whom it interacts. However, in open everyday environments, simple recognition functions such as identifying an individual are difficult because the presence and movement of a large number of people as well as unfavorable illumination and background conditions affect the robot's sensing ability. We integrated humanoid robots and ubiquitous sensors in an autonomous system to assist visitors at an Osaka Science Museum exhibit     

Inferring user intent to interact with a public service robot using bimodal information analysis

ABSTRACT

Achieving polite service with a public service robot requires it to proactively ascertain who will interact with it in human-populated environments. Enlightened by interactive inference of intentions among humans, we investigate a novel and practical interactive intention-predicting method for people using bimodal information analysis for a public service robot. Different from the traditional research, only the visual cues are used to analyze the user's attention, this method combines the RGB-D camera and laser information to perceive the user, which realizes the 360-degree range perception, and compensates for the lack of perspective using the RGB-D camera. In addition, seven kinds of interactive intent features were extracted, and a random forest regression model was trained to score the interaction intentions of the people in the field of view. Considering the inference order of two different sensors, a priority rule for intention inference is also designed. The algorithm is implemented into a robot operation system (ROS) and evaluated on our public service robot. Extensive experimental results illustrate that the proposed method enables public service robots to achieve a higher level of politeness than the traditional, passive interactivity approach in which robots wait for commands from users.     

Humans and humanoid social robots in communication contexts

As humanoid social robots are developed rapidly in recent years and experimented in social situations, comparing them to humans provides insights into practical as well as philosophical concerns. This study uses the theoretical framework of communication constraints, derived in human–human communication research, to compare whether people apply social-oriented constraints and task-oriented constraints differently to human targets versus humanoid social robot targets. A total of 230 students from the University of Hawaii at Manoa participated in the study. The participants completed a questionnaire, which determined their concern for the five communication constraints (feelings, non-imposition, disapproval, clarity, and effectiveness) in situations involving humans or robots. The results show people were more concerned with avoiding hurting the human’s feelings, avoiding inconveniencing the human interactive partner, and avoiding being disliked by the human and less concerned with avoiding hurting the robot’s feelings, avoiding inconveniencing the robot partner, and avoiding being disliked by the robot. But people did not differ in their concerns of the two task-oriented constraints (clarity and effectiveness) in response to humans versus humanoid robots. The results of the research suggest that people are more likely to emphasize the social-oriented constraints in communication with humans.     

Social interaction with robots: three questions

Robots are coming into different spheres of our daily lives, and therefore it is important that we now reflect systematically and in a comprehensive and inclusive way on the effects this may have on human interactions with other people and with machines. In Delmenhorst we held the conference “Going beyond the Laboratory.” Reflecting on the discussions of the conference, the editorial team realized a conceptual gap between the engineering sciences on the one hand and the social sciences and philosophy on the other hand. In order to initiate first steps in the direction of overcoming this divide, the editorial team decided to put forth three questions crucial for the issue of social interaction with robots and collected answers by experts in different robotics research projects. The questions are: How are we to understand the term robot autonomy in robotics and in social life? How is the idea of robot autonomy related to the limits of mathematization? I.e. is it possible, to fully express mathematically processes of social interaction? And finally, how are interactions between humans and robots in everyday life related to social institutions on a micro- and macro-level?     

A multimodal language to communicate with life-supporting robots through a touch screen and a speech interface

This article proposes a multimodal language to communicate with life-supporting robots through a touch screen and a speech interface. The language is designed for untrained users who need support in their daily lives from cost-effective robots. In this language, the users can combine spoken and pointing messages in an interactive manner in order to convey their intentions to the robots. Spoken messages include verb and noun phrases which describe intentions. Pointing messages are given when the user’s finger touches a camera image, a picture containing a robot body, or a button on a touch screen at hand which convey a location in their environment, a direction, a body part of the robot, a cue, a reply to a query, or other information to help the robot. This work presents the philosophy and structure of the language.     

基于情感交互的仿人头部机器人

本研究的目的是设计一台机器人,使它可以与人互动,并在日常生活中和常见的地方协助人类．为了 完成这些任务,机器人必须友好地显示出一些情感,表现出友好的特点和个性．依据仿生学,研制了一台仿人头部 机器人,建立了机器人的行为决策模型．该机器人具有人类的6 种基本面部表情,以及人脸检测、语音情感识别与 合成、情感行为决策等能力,能够通过机器视觉、语音交互、情感表达等方式与人进行有效的情感交互．     

Bi-directional navigation intent communication using spatial augmented reality and eye-tracking glasses for improved safety in human–robot interaction

Safety, legibility and efficiency are essential for autonomous mobile robots that interact with humans. A key factor in this respect is bi-directional communication of navigation intent, which we focus on in this article with a particular view on industrial logistic applications. In the direction robot-to-human, we study how a robot can communicate its navigation intent using Spatial Augmented Reality (SAR) such that humans can intuitively understand the robot’s intention and feel safe in the vicinity of robots. We conducted experiments with an autonomous forklift that projects various patterns on the shared floor space to convey its navigation intentions. We analyzed trajectories and eye gaze patterns of humans while interacting with an autonomous forklift and carried out stimulated recall interviews (SRI) in order to identify desirable features for projection of robot intentions. In the direction human-to-robot, we argue that robots in human co-habited environments need human-aware task and motion planning to support safety and efficiency, ideally responding to people’s motion intentions as soon as they can be inferred from human cues. Eye gaze can convey information about intentions beyond what can be inferred from the trajectory and head pose of a person. Hence, we propose eye-tracking glasses as safety equipment in industrial environments shared by humans and robots. In this work, we investigate the possibility of human-to-robot implicit intention transference solely from eye gaze data and evaluate how the observed eye gaze patterns of the participants relate to their navigation decisions. We again analyzed trajectories and eye gaze patterns of humans while interacting with an autonomous forklift for clues that could reveal direction intent. Our analysis shows that people primarily gazed on that side of the robot they ultimately decided to pass by. We discuss implications of these results and relate to a control approach that uses human gaze for early obstacle avoidance.     

Challenge: Concept of system life and its application to robotics

Artifact systems created by humans interact with the surrounding natural world and have a large-scale influence on our human lives. The most creditable concept to this critical issue of scientific and technological development seems to be “System Life” that is an innovative competence to be embodied into any artifact system for creating harmony in the world of natural entities and artifact systems interacting with each other. System life is defined as a seamless system of sensing, processing, activating and expressing mechanisms governed by system life information. This paper introduces a design approach of robots possessing system life. First, this paper presents the concept of system life comparing it with the conventional design methodology of intelligent systems. Second, the paper introduces an intelligent control methodology using the cubic neural network that the author developed in order to cope with unpredicted failures. Finally, the paper presents various intelligent robots, a skiing robot, autonomous soccer robots, a game playing robot, as new concrete artifact systems designed using the system life concept.     

Adaptive visual gesture recognition for human–robot interaction using a knowledge-based software platform

In human–human communication we can adapt or learn new gestures or new users using intelligence and contextual information. Achieving natural gesture-based interaction between humans and robots, the system should be adaptable to new users, gestures and robot behaviors. This paper presents an adaptive visual gesture recognition method for human–robot interaction using a knowledge-based software platform. The system is capable of recognizing users, static gestures comprised of the face and hand poses, and dynamic gestures of face in motion. The system learns new users, poses using multi-cluster approach, and combines computer vision and knowledge-based approaches in order to adapt to new users, gestures and robot behaviors. In the proposed method, a frame-based knowledge model is defined for the person-centric gesture interpretation and human–robot interaction. It is implemented using the frame-based Software Platform for Agent and Knowledge Management (SPAK). The effectiveness of this method has been demonstrated by an experimental human–robot interaction system using a humanoid robot ‘Robovie’.     

Accountable system design architecture for embodied AI: a focus on physical human support robots

Although the development of robot-based support systems for elderly people has become more popular, it is difficult for humans to understand the actions, plans, and behavior of autonomous robots and the reasons behind them, particularly when the robots include learning algorithms. Learning-based autonomous systems which are called AI are treated as an inherently untrustworthy ‘black box,’ because machine learning or deep learning algorithms are difficult for humans to understand. Robot systems such as assistive robots, which work closely with humans, however, should be trusted. Systems should therefore achieve accountability for all stakeholders. However, most research in this field has focused on particular systems and situations, and no general design architecture exists. In this study, we propose a new design method, focused on accountability and transparency, for learning-based robot systems. Describing the entire system is a necessary first step, and transcribing the described system for each stakeholder based on several principles is effective for achieving accountability. The method improves transparency for systems, including learning algorithms. A standing assistive robot is used as an example of the entire system to clarify which system parts require greater transparency. This study adopted the Systems Modeling Language (SysML) to describe the system and the described system is used for the information representation. Information should be represented considering the relationships between stakeholders, information, and the system interface. Because of their complexity, it is difficult for humans to understand the complete set of information available in robot systems. Systems should therefore present only the information required, depending on the situation. The stakeholder–interface relationship is also important because it is more beneficial for professionals to view information relevant to their specialized field, which would be difficult for others to understand. By contrast, the interface should be intuitive for general users. Visualization and sound are very useful means of transmitting information, with advantages and disadvantages for different circumstances. These relationships are important for achieving accountability. Finally, we show an example of implementation with a developed support system. It is confirmed that accountable systems can be designed based on the proposed design architecture.     

A Linear Affect–Expression Space Model and Control Points for Mascot-Type Facial Robots

A robot's face is its symbolic feature, and its facial expressions are the best method for interacting with people with emotional information. Moreover, a robot's facial expressions play an important role in human-robot emotional interactions. This paper proposes a general rule for the design and realization of expressions when some mascot-type facial robots are developed. Mascot-type facial robots are developed to enable friendly human feelings. The number and type of control points for six basic expressions or emotions were determined through a questionnaire. A linear affect-expression space model is provided to realize continuous and various expressions effectively, and the effects of the proposed method are shown through experiments using a simulator and an actual robot system.     

Spatial augmented reality as a method for a mobile robot to communicate intended movement

Our work evaluates a mobile robot’s ability to communicate intended movements to humans via projection of visual arrows and a simplified map. Humans utilize a variety of techniques to signal intended movement in a co-occupied space. We evaluated an augmented reality projection provided by the robot. The projection is on the floor and consists of arrows and a simplified map. Two pilots and one quasi-experiment were conducted to examine the effectiveness of visual projection of arrows by a robot for signaling intended movement. The pilot work demonstrates the effectiveness of utilizing arrows as a communication medium. The experiment examined the effectiveness of a simplified map and arrows for signaling the short-, mid-range, and long-term intended movement. Two pilot experiments confirm that arrows are an effective symbol for a robot to use to signal intent. A field experiment demonstrates that a robot can use a projected arrow and simplified map to signal its intended movement and people understand the projection for upcoming short-, medium-, and long-term movement. Augmented reality, such as projected arrows and simplified map, are an effective tool for robots to use when signaling their upcoming movement to humans. Telepresence robots in organizations, museum docents, information kiosks, hospital assistants, factories, and as members of search and rescue teams are typical applications where mobile robots reside and interact with people.     

Affective social robots

For human–robot interaction to proceed in a smooth, natural manner, robots must adhere to human social norms. One such human convention is the use of expressive moods and emotions as an integral part of social interaction. Such expressions are used to convey messages such as “I’m happy to see you” or “I want to be comforted,” and people’s long-term relationships depend heavily on shared emotional experiences. Thus, we have developed an affective model for social robots. This generative model attempts to create natural, human-like affect and includes distinctions between immediate emotional responses, the overall mood of the robot, and long-term attitudes toward each visitor to the robot, with a focus on developing long-term human–robot relationships. This paper presents the general affect model as well as particular details of our implementation of the model on one robot, the Roboceptionist. In addition, we present findings from two studies that demonstrate the model’s potential.     

人性化设计指导下的家用机器人设计探讨

以人为本是工业设计的宗旨,人性化设计指导原则为产品开发,设计,改良提供了重要启示。随着现代科技的发展,机器人为人类服务的领域已从最初的工业领域逐步发展延伸到家庭服务行列。现代人以及未来人类生活方式趋于追求自由舒适,家用机器人能帮助人们从繁琐的家务中解脱出来,它们可以代替人类实现诸如家务清洁.监管家电.看家报警等功能。家用机器人与人形成了更为密切的关系,人性化设计指导下的家用机器人设计的探讨就显得更为意义重大了。