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During social interactions, actions can be performed with different forms as a function of the mood driving them. These action forms i.e. vitality forms (VFs), have a strong influence in human interactions allowing people to immediately understand the attitude of others. Moreover, it has been demonstrated that the gentle and rude VFs expressed by a human agent influence the motor behavior of the receiver. An intriguing issue to investigate was to assess whether and how a humanoid agent, able to generate VFs, may induce the same contagion effect on the human partner. To this purpose we carried out a kinematic experiment investigating the motor behavior of participants in response to actions (taking request) performed by the iCub robot with different VFs in video and live interactive contexts. During the experiment, participants were required to pay attention to the iCub robot request and subsequently to place a ball on a specific target. Results indicate that: a) vitality forms conveyed by the iCub robot influenced the motor response of participants, modulating some kinematic parameters; b) this effect was obtained for both video and live interactive contexts; c) this effect was significantly greater in the video session compared to the live one.

The present research is innovative as we followed a user-centered approach to implement and train two working memory architectures on an industrial RB-KAIROS + robot: GRU, a state-of-the-art architecture, and WorkMATe, a biologically-inspired alternative. Although user-centered approaches are essential to create a comfortable and safe HRI, they are still rare in industrial settings. Closing this research gap, we conducted two online user studies with large heterogeneous samples. The major aim of these studies was to evaluate the RB-KAIROS + robot’s appearance, movements, and perceived memory functions before (User Study 1) and after the implementation and training of robot working memory (User Study 2). In User Study 1, we furthermore explored participants’ ideas about robot memory and what aspects of the robot’s movements participants found positive and what aspects they would change. The effects of participants’ demographic background and attitudes were controlled for. In User Study 1, participants’ overall evaluations of the robot were moderate. Participant age and negative attitudes toward robots led to more negative robot evaluations. According to exploratory analyses, these effects were driven by perceived low experience with robots. Participants expressed clear ideas of robot memory and precise suggestions for a safe, efficient, and comfortable robot navigation which are valuable for further research and development. In User Study 2, the implementation of WorkMATe and GRU led to more positive evaluations of perceived robot memory, but not of robot appearance and movements. Participants’ robot evaluations were driven by their positive views of robots. Our results demonstrate that considering potential users’ views can greatly contribute to an efficient and positively perceived robot navigation, while users’ experience with robots is crucial for a positive HRI.

A key goal in human-robot interaction (HRI) is to design scenarios between humanoid robots and humans such that the interaction is perceived as collaborative and natural, yet safe and comfortable for the human. Human skills like verbal and non-verbal communication are essential elements as humans tend to attribute social behaviors to robots. However, aspects like the uncanny valley and different technical affinity levels can impede the success of HRI scenarios, which has consequences on the establishment of long-term interaction qualities like trust and rapport. In the present study, we investigate the impact of a humanoid robot on human emotional responses during the performance of a cognitively demanding task. We set up three different conditions for the robot with increasing levels of social cue expressions in a between-group study design. For the analysis of emotions, we consider the eye gaze behavior, arousal-valence for affective states, and the detection of action units. Our analysis reveals that the participants display a high tendency toward positive emotions in presence of a robot with clear social skills compared to other conditions, where we show how emotions occur only at task onset. Our study also shows how different expression levels influence the analysis of the robots' role in HRI. Finally, we critically discuss the current trend of automatized emotion or affective state recognition in HRI and demonstrate issues that have direct consequences on the interpretation and, therefore, claims about human emotions in HRI studies.

Partners have to build a shared understanding of their environment in everyday collaborative tasks by aligning their perceptions and establishing a common ground. This is one of the aims of shared perception: revealing characteristics of the individual perception to others with whom we share the same environment. In this regard, social cognitive processes, such as joint attention and perspective-taking, form a shared perception. From a Human-Robot Interaction (HRI) perspective, robots would benefit from the ability to establish shared perception with humans and a common understanding of the environment with their partners. In this work, we wanted to assess whether a robot, considering the differences in perception between itself and its partner, could be more effective in its helping role and to what extent this improves task completion and the interaction experience. For this purpose, we designed a mathematical model for a collaborative shared perception that aims to maximise the collaborators’ knowledge of the environment when there are asymmetries in perception. Moreover, we instantiated and tested our model via a real HRI scenario. The experiment consisted of a cooperative game in which participants had to build towers of Lego bricks, while the robot took the role of a suggester. In particular, we conducted experiments using two different robot behaviours. In one condition, based on shared perception, the robot gave suggestions by considering the partners’ point of view and using its inference about their common ground to select the most informative hint. In the other condition, the robot just indicated the brick that would have yielded a higher score from its individual perspective. The adoption of shared perception in the selection of suggestions led to better performances in all the instances of the game where the visual information was not a priori common to both agents. However, the subjective evaluation of the robot’s behaviour did not change between conditions.

Across three experiments (N = 302), we explored whether people cognitively elaborate humanoid robots as human- or object-like. In doing so, we relied on the inversion paradigm, which is an experimental procedure extensively used by cognitive research to investigate the elaboration of social (vs. non-social) stimuli. Overall, mixed-model analyses revealed that full-bodies of humanoid robots were subjected to the inversion effect (body-inversion effect) and, thus, followed a configural processing similar to that activated for human beings. Such a pattern of finding emerged regardless of the similarity of the considered humanoid robots to human beings. That is, it occurred when considering bodies of humanoid robots with medium (Experiment 1), high and low (Experiment 2) levels of human likeness. Instead, Experiment 3 revealed that only faces of humanoid robots with high (vs. low) levels of human likeness were subjected to the inversion effects and, thus, cognitively anthropomorphized. Theoretical and practical implications of these findings for robotic and psychological research are discussed.

One of the fundamental prerequisites for effective collaborations between interactive partners is the mutual sharing of the attentional focus on the same perceptual events. This is referred to as joint attention. In psychological, cognitive, and social sciences, its defining elements have been widely pinpointed. Also the field of human-robot interaction has extensively exploited joint attention which has been identified as a fundamental prerequisite for proficient human-robot collaborations. However, joint attention between robots and human partners is often encoded in prefixed robot behaviours that do not fully address the dynamics of interactive scenarios. We provide autonomous attentional behaviour for robotics based on a multi-sensory perception that robustly relocates the focus of attention on the same targets the human partner attends. Further, we investigated how such joint attention between a human and a robot partner improved with a new biologically-inspired memory-based attention component. We assessed the model with the humanoid robot iCub involved in performing a joint task with a human partner in a real-world unstructured scenario. The model showed a robust performance on capturing the stimulation, making a localisation decision in the right time frame, and then executing the right action. We then compared the attention performance of the robot against the human performance when stimulated from the same source across different modalities (audio-visual and audio only). The comparison showed that the model is behaving with temporal dynamics compatible with those of humans. This provides an effective solution for memory-based joint attention in real-world unstructured environments. Further, we analyzed the localisation performances (reaction time and accuracy), the results showed that the robot performed better in an audio-visual condition than an audio only condition. The performance of the robot in the audio-visual condition was relatively comparable with the behaviour of the human participants whereas it was less efficient in audio-only localisation. After a detailed analysis of the internal components of the architecture, we conclude that the differences in performance are due to egonoise which significantly affects the audio-only localisation performance.

In our everyday lives we regularly engage in complex, personalized, and adaptive interactions with our peers. To recreate the same kind of rich, human-like interactions, a social robot should be aware of our needs and affective states and continuously adapt its behavior to them. Our proposed solution is to have the robot learn how to select the behaviors that would maximize the pleasantness of the interaction for its peers. To make the robot autonomous in its decision making, this process could be guided by an internal motivation system. We wish to investigate how an adaptive robotic framework of this kind would function and personalize to different users. We also wish to explore whether the adaptability and personalization would bring any additional richness to the human-robot interaction (HRI), or whether it would instead bring uncertainty and unpredictability that would not be accepted by the robot's human peers. To this end, we designed a socially adaptive framework for the humanoid robot iCub. As a result, the robot perceives and reuses the affective and interactive signals from the person as input for the adaptation based on internal social motivation. We strive to investigate the value of the generated adaptation in our framework in the context of HRI. In particular, we compare how users will experience interaction with an adaptive versus a non-adaptive social robot. To address these questions, we propose a comparative interaction study with iCub whereby users act as the robot's caretaker, and iCub's social adaptation is guided by an internal comfort level that varies with the stimuli that iCub receives from its caretaker. We investigate and compare how iCub's internal dynamics would be perceived by people, both in a condition when iCub does not personalize its behavior to the person, and in a condition where it is instead adaptive. Finally, we establish the potential benefits that an adaptive framework could bring to the context of repeated interactions with a humanoid robot.

Deception is a complex social skill present in human interactions. Many social professions such as teachers, therapists and law enforcement officers leverage on deception detection techniques to support their work activities. Robots with the ability to autonomously detect deception could provide an important aid to human-human and human-robot interactions. The objective of this work is to demonstrate the possibility to develop a lie detection system that could be implemented on robots. To this goal, we focus on human and human robot interaction to understand if there is a difference in the behavior of the participants when lying to a robot or to a human. Participants were shown short movies of robberies and then interrogated by a human and by a humanoid robot “detectives.” According to the instructions, subjects provided veridical responses to half of the question and false replies to the other half. Behavioral variables such as eye movements, time to respond and eloquence were measured during the task, while personality traits were assessed before experiment initiation. Participant's behavior showed strong similarities during the interaction with the human and the humanoid. Moreover, the behavioral features were used to train and test a lie detection algorithm. The results show that the selected behavioral variables are valid markers of deception both in human-human and in human-robot interactions and could be exploited to effectively enable robots to detect lies.

In the industry of the future, so as in healthcare and at home, robots will be a familiar presence. Since they will be working closely with human operators not always properly trained for human-machine interaction tasks, robots will need the ability of automatically adapting to changes in the task to be performed or to cope with variations in how the human partner completes the task. The goal of this work is to make a further step toward endowing robot with such capability. To this purpose, we focus on the identification of relevant time instants in an observed action, called dynamic instants, informative on the partner's movement timing, and marking instants where an action starts or ends, or changes to another action. The time instants are temporal locations where the motion can be ideally segmented, providing a set of primitives that can be used to build a temporal signature of the action and finally support the understanding of the dynamics and coordination in time. We validate our approach in two contexts, considering first a situation in which the human partner can perform multiple different activities, and then moving to settings where an action is already recognized and shows a certain degree of periodicity. In the two contexts we address different challenges. In the first one, working in batch on a dataset collecting videos of a variety of cooking activities, we investigate whether the action signature we compute could facilitate the understanding of which type of action is occurring in front of the observer, with tolerance to viewpoint changes. In the second context, we evaluate online on the robot iCub the capability of the action signature in providing hints to establish an actual temporal coordination during the interaction with human participants. In both cases, we show promising results that speak in favor of the potentiality of our approach.

Infertility is a potential side effect of radiotherapy and significantly affects the quality of life for adolescent cancer survivors. Very few studies have addressed in pubertal models the mechanistic events that could be targeted to provide protection from gonadotoxicity and data on potential radioprotective treatments in this peculiar period of life are elusive. In this study, we utilized an in vitro model of the mouse pubertal testis to investigate the efficacy of crocetin to counteract ionizing radiation (IR)-induced injury and potential underlying mechanisms. Present experiments provide evidence that exposure of testis fragments from pubertal mice to 2 Gy X-rays induced extensive structural and cellular damage associated with overexpression of PARP1, PCNA, SOD2 and HuR and decreased levels of SIRT1 and catalase. A twenty-four hr exposure to 50 μM crocetin pre- and post-IR significantly reduced testis injury and modulated the response to DNA damage and oxidative stress. Nevertheless, crocetin treatment did not counteract the radiation-induced changes in the expression of SIRT1, p62 and LC3II. These results increase the knowledge of mechanisms underlying radiation damage in pubertal testis and establish the use of crocetin as a fertoprotective agent against IR deleterious effects in pubertal period.

Polycystic ovary syndrome (PCOS) is a complex metabolic disorder associated with female infertility. Based on energy and antioxidant regulatory functions of carnitines, we investigated whether acyl-L-carnitines improve PCOS phenotype in a mouse model induced by dehydroepiandrosterone (DHEA). CD1 mice received DHEA for 20 days along with two different carnitine formulations: one containing L-carnitine (LC) and acetyl-L-carnitine (ALC), and the other one containing also propionyl-L-carnitine (PLC). We evaluated estrous cyclicity, testosterone level, ovarian follicle health, ovulation rate and oocyte quality, collagen deposition, lipid droplets, and 17ß-HSD IV (17 beta-hydroxysteroid dehydrogenase type IV) expression. Moreover, we analyzed protein expression of SIRT1, SIRT3, SOD2 (superoxide dismutase 2), mitochondrial transcriptional factor A (mtTFA), RAGE (receptor for AGEs), GLO2 (glyoxalase 2) and ovarian accumulation of MG-AGEs (advanced glycation end-products formed by methylglyoxal). Both carnitine formulations ameliorated ovarian PCOS phenotype and positively modulated antioxidant molecular pathways in the ovarian microenvironment. Addition of PLC to LC-ALC formulation mitigated intraovarian MG-AGE accumulation and increased mtTFA expression. In conclusion, our study supports the hypothesis that oral administration of acyl-L-carnitines alleviates ovarian dysfunctions associated with this syndrome and that co-administration of PLC provides better activity. Molecular mechanisms underlying these effects include anti-oxidant/glycative activity and potentiation of mitochondria.

Advanced glycation end-products (AGEs) are involved in the pathogenesis and consequences of polycystic ovary syndrome (PCOS), a complex metabolic disorder associated with female infertility. The most powerful AGE precursor is methylglyoxal (MG), a byproduct of glycolysis, that is detoxified by the glyoxalase system. By using a PCOS mouse model induced by administration of dehydroepiandrosterone (DHEA), we investigated whether MG-dependent glycative stress contributes to ovarian PCOS phenotype and explored changes in the Sirtuin 1 (SIRT1) functional network regulating mitochondrial functions and cell survival. In addition to anovulation and reduced oocyte quality, DHEA ovaries revealed altered collagen deposition, increased vascularization, lipid droplets accumulation and altered steroidogenesis. Here we observed increased intraovarian MG-AGE levels in association with enhanced expression of receptor for AGEs (RAGEs) and deregulation of the glyoxalase system, hallmarks of glycative stress. Moreover, DHEA mice exhibited enhanced ovarian expression of SIRT1 along with increased protein levels of SIRT3 and superoxide dismutase 2 (SOD2), and decreased peroxisome proliferator-activated receptor gamma co-activator 1 alpha (PGC1α), mitochondrial transcriptional factor A (mtTFA) and translocase of outer mitochondrial membrane 20 (TOMM20). Finally, the presence of autophagy protein markers and increased AMP-activated protein kinase (AMPK) suggested the involvement of SIRT1/AMPK axis in autophagy activation. Overall, present findings demonstrate that MG-dependent glycative stress is involved in ovarian dysfunctions associated to PCOS and support the hypothesis of a SIRT1-dependent adaptive response.

One of the fundamental skills supporting safe and comfortable interaction between humans is their capability to understand intuitively each other’s actions and intentions. At the basis of this ability is a special-purpose visual processing that human brain has developed to comprehend human motion. Among the first “building blocks” enabling the bootstrapping of such visual processing is the ability to detect movements performed by biological agents in the scene, a skill mastered by human babies in the first days of their life. In this paper, we present a computational model based on the assumption that such visual ability must be based on local low-level visual motion features, which are independent of shape, such as the configuration of the body and perspective. Moreover, we implement it on the humanoid robot iCub, embedding it into a software architecture that leverages the regularities of biological motion also to control robot attention and oculomotor behaviors. In essence, we put forth a model in which the regularities of biological motion link perception and action enabling a robotic agent to follow a human-inspired sensory-motor behavior. We posit that this choice facilitates mutual understanding and goal prediction during collaboration, increasing the pleasantness and safety of the interaction.

Modern transport aircraft wings have reached near-peak levels of energy-efficiency and there is still margin for further relevant improvements. A promising strategy for improving aircraft efficiency is to change the shape of the aircraft wing in flight in order to maximize its aerodynamic performance under all operative conditions. In the present work, this has been developed in the framework of the Clean Sky 2 (REG-IADP) European research project, where the authors focused on the design of a multifunctional twistable trailing-edge for a Natural Laminar Flow (NLF) wing. A multifunctional wing trailing-edge is used to improve aircraft performance during climb and off-design cruise conditions in response to variations in speed, altitude and other flight parameters. The investigation domain of the novel full-scale device covers 5.15 m along the wing span and the 10% of the local wing chord. Concerning the wing trailing-edge, the preliminary structural and kinematic design process of the actuation system is completely addressed: three rotary brushless motors (placed in root, central and tip sections) are required to activate the inner mechanisms enabling different trailing-edge morphing modes. The structural layout of the thin-walled closed-section composite trailing-edge represents a promising concept, meeting both the conflicting requirements of load-carrying capability and shape adaptivity. Actuation system performances and aeroelastic deformations, considering both operative aerodynamic and limit load conditions, prove the potential of the proposed structural concept to be energy efficient and lightweight for real aircraft implementation. Finally, the performance assessment of the outer natural laminar flow (NLF) wing retrofitted with the multifunctional trailing-edge is performed by high-fidelity aerodynamic analyses. For such an NLF wing, this device can improve airplane aerodynamic efficiency during high speed climb conditions.