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In the field of robotics, there is a growing awareness of the importance of benchmarking [1], [2]. Benchmarking not only allows the assessment and comparison of the performance of different technologies but also defines and supports the standardization and regulation processes during their introduction to the market. Its importance has been recently emphasized by the adoption of the technology readiness levels (TRLs) in the Horizon 2020 information and communication technologies by the European Union as an important guideline to assess when a technology can shift from one TRL to the other. The objective of this article is to define the basis of a benchmarking scheme for the assessment of bipedal locomotion that could be applied and shared across different research communities. ; European Commission Seventh Framework Program, and COST

This study suggests an innovative way of using an intelligent robot to support speech therapy for hearing impaired children through play. Although medical technology (e.g., hearing aid, cochlear implant) for children with hear-ing impairment has advanced significantly, the amplification itself does not provide optimal development of hearing and speaking; it must be combined with specialized therapy. The present study focuses on the use of the humanoid robot NAO in auditory-verbal therapy, an approach to the development of audi-tory and verbal skills, which does not allow lipreading or other non-verbal cues to facilitate communication. NAO does not have a human mouth and therefore children with hearing impairment cannot do lipreading; this unique characteris-tic of the technology has been successfully used in the study to create playful and engaging auditory-verbal therapy sessions for six kindergarten hearing im-paired children, allowing them to improve their ability to follow instructions us-ing the hearing aid/ cochlear implant rather than visual clues in the environ-ment. Our results, although preliminary, seem to encourage further research in supporting hearing-impaired children via play with intelligent robots. ; This work has been partly supported by the project that has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 739578 (RISE – Call: H2020-WIDESPREAD-01-2016-2017-TeamingPhase2) and the Government of the Republic of Cyprus through the Directorate General for European Programmes, Coordination and Development.

The version of record is available online at: https://doi.org/10.1007/s10514-021-09976-7 ; This paper proposes to enrich robot motion data with trajectory curvature information. To do so,we use an approximate implementation of a topological feature named writhe, which measures the curling of a closed curve around itself, and its analog feature for two closed curves, namely the linking number. Despite these features have been established for closed curves, their definition allows for a discrete calculation that is well-defined for non-closed curves and can thus provide information about how much a robot trajectory is curling around a line in space. Such lines can be predefined by a user, observed by vision or, in our case, inferred as virtual lines in space around which the robot motion is curling. We use these topological features to augment the data of a trajectory encapsulated as a Movement Primitive (MP). We propose a method to determine how many virtual segments best characterize a trajectory and then find such segments. This results in a generative model that permits modulating curvature to generate new samples, while still staying within the dataset distribution and being able to adapt to contextual variables. ; This work has been carried out within the project CLOTHILDE ("CLOTH manIpulation Learning from DEmonstrations") funded by the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (Advanced Grant agreement No 741930). Research at IRI is also supported by the Spanish State Research Agency through the Mar ́ıa de Maeztu Seal of Excellence to IRI MDM-2016-0656 ; Peer Reviewed ; Postprint (author's final draft)

© 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. ; Learning from Demonstration (LfD) is a paradigm that allows robots to learn complex manipulation tasks that can not be easily scripted, but can be demonstrated by a human teacher. One of the challenges of LfD is to enable robots to acquire skills that can be adapted to different scenarios. In this paper, we propose to achieve this by exploiting the variations in the demonstrations to retrieve an adaptive and robust policy, using Gaussian Process (GP) models. Adaptability is enhanced by incorporating task parameters into the model, which encode different specifications within the same task. With our formulation, these parameters can be either real, integer, or categorical. Furthermore, we propose a GP design that exploits the structure of replications, i.e., repeated demonstrations with identical conditions within data. Our method significantly reduces the computational cost of model fitting in complex tasks, where replications are essential to obtain a robust model. We illustrate our approach through several experiments on a handwritten letter demonstration dataset. ; This work has been partially funded by the European Union Horizon 2020 Programme under grant agreement no. 741930 (CLOTHILDE) and by the Spanish State Research Agency through the Mar ́ıa de Maeztu Seal of Excellence to IRI [MDM-2016-0656]. ; Peer Reviewed ; Postprint (author's final draft)

Roboticists developing socially interactive robots seek to design them in such a way that humans will readily anthropomorphize them. For this anthropomorphizing to occur, robots need to display emotion‐like responses to elicit empathy from the person, so as to enable social interaction. This article focuses on roboticists' efforts to create emotion‐like responses in humanoid robots. In particular, I investigate the extent to which the cultural dimensions of emotion and empathy are factored into these endeavors. Recent research suggests that mirror neurons or other brain structures may have a role to play in empathy and imitation. Notwithstanding this, the effect of sociocultural experience in shaping appropriate empathic responses and expectations is also crucial. More broadly, this article highlights how we are literally anthropomorphizing technology, even as the complexity of technology and the role it plays in our lives grows. Both the actual design process and the understanding of how technology shapes our daily lives are core applied dimensions of this work, from carrying out the research to capturing the critical implications of these technological innovations.

According to the Swedish science fiction TV series Äkta människor (Real Humans, SVT and Matador film 2012-2014), humanoid robots called "hubots" are replacing the human workforce in care work and assembly line industries. Against the backdrop of current debates about immigration and citizenship in the Nordic countries, this article does a close, contextual reading of the series, exploring how the hubots influence work and family life. We are particularly interested in how hubots tie in with the cultural circulation of aff ect in relation to Otherness and how responses towards the "not-quite" human or dehumanized Other are negotiated in present-day Nordic cultural imaginaries. What kinds of affects are at stake in how Äkta människor takes up and interacts with debates about immigrant workers and the "not-quite" human? To answer these questions, the article develops the notion of "affective imaginaries" as an analytical tool for understanding the exchange between popular culture and political debate. ; publishedVersion

Jennifer Robertson's Robo Sapiens Japanicus: Robots, Gender, Family, and the Japanese Nation assesses the robot phenomenon in Japan within the last decade. Offering sustained critiques on contemporary techno-fix narratives, Robertson reveals how humanoid robots are designed and deployed to reify conservative values under the guise of technological advancements. Robertson's impressive ethnographic project weaves together robots of science fact and fiction, leaving readers to interrogate how humanoids, androids, gynoids, and cyborgs both challenge and reify existing social structures across the globe.

Life-likeness is a property that can be used both to deceive people that a robot is more intelligent than it is or to facilitate the natural communication with humans. Over the years, different criteria have guided the design of intelligent systems, ranging from attempts to produce human-like language to trying to make a robot look like an actual human. We outline some relevant historical developments that all rely on different forms of mimicry of human life or intelligence. Many such approaches have been to some extent successful. However, we want to argue that there are ways to exploit aspects of life-likeness without deception. A life-like robot has advantages in communicating with humans, not because we believe it to be alive, but rather because we react instinctively to certain aspects of life-like behavior as this can make a robot easier to understand and allows us to better predict its actions. Although there may be reasons for trying to design robots that look exactly like humans for specific research purposes, we argue that it is subtle behavioral cues that are important for understandable robots rather than life-likeness in itself. To this end, we are developing a humanoid robot that will be able to show human-like movements while still looking decidedly robotic, thus exploiting the our ability to understand the behaviors of other people based on their movements.

Robots are the next wave in service technology; however, this advanced technology is not perfect. This research examines how social perceptions regarding the warmth and competence of service robots influence consumer reactions to service failures and recovery efforts by robots. We argue that humanoid (vs. nonhumanoid) service robots are more strongly associated with warmth (whereas competence does not differ). This tendency to expect greater warmth from humanoid robots has important consequences for service firms: (i) consumers are more dissatisfied due to lack of warmth following a process failure caused by a humanoid (vs. nonhumanoid; Study 1); (ii) humanoids (but not nonhumanoids) can recover a service failure by themselves via sincere apology, restoring perceptions of warmth (Study 2A); (iii) humanoids (but not nonhumanoids) can also effectively provide explanations as a recovery tactic (Study 2B); and, importantly, (iv) human intervention can be used to mitigate dissatisfaction following inadequate recovery by a nonhumanoid robot (Study 3), supporting the notion of human-robot collaboration. Taken together, this research offers theoretical implications for robot anthropomorphism and practical implications for firms employing service robots.

Today, beyond being just technological objects, artificial intelligence and robots create a multidimensional relationship network within the social structure. This multidimensional network of relationships includes human actors such as mathematicians, engineers, bankers, doctors, soldiers, students, and teachers and non-human smart actors such as chatbots, virtual assistants, autonomous vehicles, translation programs, CCTV systems, drones, humanoid robots, and smart home robots. This study is aimed to determine the perception of function towards artificial intelligence and robots of individuals who use the said technology and follow the developments and whether this perception changes according to some variables. Some data on the perception of function towards artificial intelligence and robots are handled in line with Merton's functionality perspective. Qualitative and quantitative methods obtained the data, and it was observed that the perception of function towards the technology in question differs according to the people's expectations, needs, and positions. It is thought that the data obtained will be useful to the literature and the experts on the subject.

Technology is improving day by day and every new face of it is engrossing, making applied science astonishment. Robotics and Artificial Intelligence have taken the world beyond automation. Automation was once considered as a challenge, but now the same technology has stunned the whole world, with the transformation of vision to the reality of live cell robots. In this modern era, evolutionary algorithms with Artificial Intelligence have made an impact on the automation and the creation of rare live-cell species by integrating biological aspects of frog cells. It would be thus useful in various domains to build technologies using self-renewing, and biocompatible materials of which the ideal candidates are living themselves. Thus, this paper presents a live cell robot named Xenobots, its design method, formation, applications, and transformation of live cell robots to humanoid robots that mimic the human brain.

Einleitung -- 1 Industrielle und soziale Robotertypen -- 2 Soziologische Theorieansätze – "Wesensbestimmung des Sozialen" – Ent-anthropozentrische Personalitätsbekundungen in der soziologischen Theoriebildung -- 3 Zentrisch positionierte Wesen -- 4 Exzentrisch positionierte Wesen -- 5 Formen der Anwesenheit sozialer Akteure -- 6 Methodenteil -- 7 Empirische Untersuchung des Idling und Facetrack Modus -- 8 Empirische Untersuchung Teleoperation.

The first industrial robot was set along the production line in Japan in 1969. Through the miracle recovery of the great economic growth in post-war Japan, more robots were developed. Today, we see robots operating in many environments other than indoor assembly lines. Meanwhile, robots truly have come of age as a result of amazing advances in programming (artificial intelligence) and sensor-information technology. In the future, we will find more super-intelligent humanoids coexisting with us, and cities will be structured as robot-friendly environments where not only humanoids but ubiquitous machines of all kinds with built-in computer, sensors, and actuators will enhance and supplement human existence in countless ways.