Telepresence Mobile Robots Design and Control for Social Interaction.
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ABSTRACT:
SUBMITTER: Tuli TB
PROVIDER: S-EPMC7358301 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:We present a novel functional magnetic resonance imaging paradigm for second-person neuroscience. The paradigm compares a human social interaction (human-human interaction, HHI) to an interaction with a conversational robot (human-robot interaction, HRI). The social interaction consists of 1 min blocks of live bidirectional discussion between the scanned participant and the human or robot agent. A final sample of 21 participants is included in the corpus comprising physiological (blood oxygen level-dependent, respiration and peripheral blood flow) and behavioural (recorded speech from all interlocutors, eye tracking from the scanned participant, face recording of the human and robot agents) data. Here, we present the first analysis of this corpus, contrasting neural activity between HHI and HRI. We hypothesized that independently of differences in behaviour between interactions with the human and robot agent, neural markers of mentalizing (temporoparietal junction (TPJ) and medial prefrontal cortex) and social motivation (hypothalamus and amygdala) would only be active in HHI. Results confirmed significantly increased response associated with HHI in the TPJ, hypothalamus and amygdala, but not in the medial prefrontal cortex. Future analysis of this corpus will include fine-grained characterization of verbal and non-verbal behaviours recorded during the interaction to investigate their neural correlates. This article is part of the theme issue 'From social brains to social robots: applying neurocognitive insights to human-robot interaction'.
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Project description:In previous experiments, a back-off movement was introduced as a motion strategy of robots to facilitate the order of passage at bottlenecks in human-robot spatial interaction. In this article we take a closer look at the appropriate application of motion parameters that make the backward movement legible. Related works in distance perception, size-speed illusions, and viewpoint-based legibility considerations suggest a relationship between the size of the robot and the observer's perspective on the expected execution of this movement. We performed a participant experiment (N = 50) in a virtual reality environment where participants adjusted the minimum required back-off length and preferred back-off speed as a result of the robot size, and the viewpoint of the back-off movement. We target a model-based approach on how appropriate back-off design translates to different sized robots and observer's viewpoints. Thus, we allow the application of back-off in a variety of autonomous moving systems. The results show a significant correlation between the increasingly expected back-off lengths with increasing robot size, but only weak effects of the viewpoint on the requirements of this movement. An exploratory analysis suggests that execution time might be a promising parameter to consider for the design of legible motion.
| S-EPMC7993606 | biostudies-literature
Project description:Social learning is a powerful method for cultural propagation of knowledge and skills relying on a complex interplay of learning strategies, social ecology and the human propensity for both learning and tutoring. Social learning has the potential to be an equally potent learning strategy for artificial systems and robots in specific. However, given the complexity and unstructured nature of social learning, implementing social machine learning proves to be a challenging problem. We study one particular aspect of social machine learning: that of offering social cues during the learning interaction. Specifically, we study whether people are sensitive to social cues offered by a learning robot, in a similar way to children's social bids for tutoring. We use a child-like social robot and a task in which the robot has to learn the meaning of words. For this a simple turn-based interaction is used, based on language games. Two conditions are tested: one in which the robot uses social means to invite a human teacher to provide information based on what the robot requires to fill gaps in its knowledge (i.e. expression of a learning preference); the other in which the robot does not provide social cues to communicate a learning preference. We observe that conveying a learning preference through the use of social cues results in better and faster learning by the robot. People also seem to form a "mental model" of the robot, tailoring the tutoring to the robot's performance as opposed to using simply random teaching. In addition, the social learning shows a clear gender effect with female participants being responsive to the robot's bids, while male teachers appear to be less receptive. This work shows how additional social cues in social machine learning can result in people offering better quality learning input to artificial systems, resulting in improved learning performance.
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Project description:IntroductionSocial isolation is a significant issue in aged care settings (eg, long-term care (LTC) and hospital) and is associated with adverse outcomes such as reduced well-being and loneliness. Loneliness is linked with depression, anxiety, cognitive decline, weakened immune system, poor physical health, poor quality of life and mortality. The use of robotic assistance may help mitigate social isolation and loneliness. Although telepresence robots have been used in healthcare settings, a comprehensive review of studies focusing on their use in aged care for reducing social isolation requires further investigation. This scoping review will focus on the use of telepresence robots to support social connection of older people in care settings.Methods and analysisThis scoping review will follow Joanna Briggs Institute scoping review methodology. The review team consists of patient partners and family partners, a nurse researcher and a group of students. In the scoping review, we will search the following databases: MEDLINE (Ovid), CINAHL, PsycINFO (EBSCO), Web of Science and ProQuest Dissertations & Theses Global. Google and Google Scholar will be used to search for additional literature. A handsearch will be conducted using the reference lists of included studies to identify additional relevant articles. The scoping review will consider studies of using a telepresence robotic technology with older adults in care settings (ie, LTC and hospital), published in English.Ethics and disseminationSince the methodology of the study consists of collecting data from publicly available articles, it does not require ethics approval. By examining the current state of using telepresence to support older people in care settings, this scoping review can offer useful insight into users' needs (eg, patients' and care providers' needs) and inform future research and practice. We will share the scoping review results through conference presentations and an open access publication in a peer-reviewed journal.
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Project description:The ability to recognize the surface type is crucial for both indoor and outdoor mobile robots. Knowing the surface type can help indoor mobile robots move more safely and adjust their movement accordingly. However, recognizing surface characteristics is challenging since similar planes can appear substantially different; for instance, carpets come in various types and colors. To address this inherent uncertainty in vision-based surface classification, this study first generates a new, unique data set composed of 2,081 surface images (carpet, tiles, and wood) captured in different indoor environments. Secondly, the pre-trained state-of-the-art deep learning models, namely InceptionV3, VGG16, VGG19, ResNet50, Xception, InceptionResNetV2, and MobileNetV2, were utilized to recognize the surface type. Additionally, a lightweight MobileNetV2-modified model was proposed for surface classification. The proposed model has approximately four times fewer total parameters than the original MobileNetV2 model, reducing the size of the trained model weights from 42 MB to 11 MB. Thus, the proposed model can be used in robotic systems with limited computational capacity and embedded systems. Lastly, several optimizers, such as SGD, RMSProp, Adam, Adadelta, Adamax, Adagrad, and Nadam, are applied to distinguish the most efficient network. Experimental results demonstrate that the proposed model outperforms all other applied methods and existing approaches in the literature by achieving 99.52% accuracy and an average score of 99.66% in precision, recall, and F1-score. In addition to this, the proposed lightweight model was tested in real-time on a mobile robot in 11 scenarios consisting of various indoor environments such as offices, hallways, and homes, resulting in an accuracy of 99.25%. Finally, each model was evaluated in terms of model loading time and processing time. The proposed model requires less loading and processing time than the other models.
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Project description:To better understand the role of tensegrity structures in biological systems and their application to robotics, the Dynamic Tensegrity Robotics Lab at NASA Ames Research Center, Moffett Field, CA, USA, has developed and validated two software environments for the analysis, simulation and design of tensegrity robots. These tools, along with new control methodologies and the modular hardware components developed to validate them, are presented as a system for the design of actuated tensegrity structures. As evidenced from their appearance in many biological systems, tensegrity ('tensile-integrity') structures have unique physical properties that make them ideal for interaction with uncertain environments. Yet, these characteristics make design and control of bioinspired tensegrity robots extremely challenging. This work presents the progress our tools have made in tackling the design and control challenges of spherical tensegrity structures. We focus on this shape since it lends itself to rolling locomotion. The results of our analyses include multiple novel control approaches for mobility and terrain interaction of spherical tensegrity structures that have been tested in simulation. A hardware prototype of a spherical six-bar tensegrity, the Reservoir Compliant Tensegrity Robot, is used to empirically validate the accuracy of simulation.
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Project description:Conventionally, robot morphologies are developed through simulations and calculations, and different control methods are applied afterwards. Assuming that simulations and predictions are simplified representations of our reality, how sure can roboticists be that the chosen morphology is the most adequate for the possible control choices in the real-world? Here we study the influence of the design parameters in the creation of a robot with a Bayesian morphology-control (MC) co-optimization process. A robot autonomously creates child robots from a set of possible design parameters and uses Bayesian Optimization (BO) to infer the best locomotion behavior from real world experiments. Then, we systematically change from an MC co-optimization to a control-only (C) optimization, which better represents the traditional way that robots are developed, to explore the trade-off between these two methods. We show that although C processes can greatly improve the behavior of poor morphologies, such agents are still outperformed by MC co-optimization results with as few as 25 iterations. Our findings, on one hand, suggest that BO should be used in the design process of robots for both morphological and control parameters to reach optimal performance, and on the other hand, point to the downfall of current design methods in face of new search techniques.
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Project description:Aim:To explore how an AV1 telepresence robot helps school-aged children and adolescents with cancer to remain socially and academically connected with their school classes during cancer treatment. Design:Qualitative pilot study. Methods:Data were collected through semi-structured interviews with school-aged children and adolescents (N = 3, 12-14 years) diagnosed with cancer, their parents (N = 3), teachers (N = 2), classmates (12-14 years, N = 15, focus group interviews) and healthcare professionals (N = 4). Participant observation was performed in the child or adolescents' homes and in the classrooms during education participation via an AV1 telepresence robot. Results:Five themes emerged: expectations, sociality, learning, spatiality and technology. Participants experienced the robots as facilitating social interaction processes with classmates and inclusion in learning activities, reducing their sense of loneliness and lacking behind educationally. Nevertheless, multiple factors determine whether the robot is perceived as exclusive, including the technical functionality of the robot, spatiality in the classroom and mutual expectations of the parties involved.
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Project description:Worldwide cardiovascular diseases such as stroke and heart disease are the leading cause of mortality. While guidewire/catheter-based minimally invasive surgery is used to treat a variety of cardiovascular disorders, existing passive guidewires and catheters suffer from several limitations such as low steerability and vessel access through complex geometry of vasculatures and imaging-related accumulation of radiation to both patients and operating surgeons. To address these limitations, magnetic soft continuum robots (MSCRs) in the form of magnetic field-controllable elastomeric fibers have recently demonstrated enhanced steerability under remotely applied magnetic fields. While the steerability of an MSCR largely relies on its workspace-the set of attainable points by its end effector-existing MSCRs based on embedding permanent magnets or uniformly dispersing magnetic particles in polymer matrices still cannot give optimal workspaces. The design and optimization of MSCRs have been challenging because of the lack of efficient tools. Here, we report a systematic set of model-based evolutionary design, fabrication, and experimental validation of an MSCR with a counterintuitive nonuniform distribution of magnetic particles to achieve an unprecedented workspace. The proposed MSCR design is enabled by integrating a theoretical model and the genetic algorithm. The current work not only achieves the optimal workspace for MSCRs but also provides a powerful tool for the efficient design and optimization of future magnetic soft robots and actuators.
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Project description:There is a growing interest in employing telepresence robots in different educational contexts due to their great potentials to enhance and improve educational experiences for remote learners. However, there is little use of telepresence robots in virtual transnational education contexts in developing countries. There is a lack of knowledge about university academics’ perceptions regarding the future use of telepresence robots to enhance virtual transnational education contexts. This exploratory research aims to fill this gap by seeking to have evidence-based information on whether telepresence robots as a new emerging technology is perceived among university academics as a useful tool for enhancing virtual transnational education or not. This study also seeks to better understand university academics’ perceptions of obstacles that may hinder them from using telepresence robots and the support that they will need. A sample of 46 Egyptian university academics participated in this study. The results of the study revealed that the academics perceived telepresence robots to have a great potential to enhance virtual transnational education. The academics also perceived telepresence robotics to have positive effects on educational activities. Furthermore, the participants indicated a number of barriers regarding integrating telepresence robotics into the teaching and learning activities and identified the types of support they will need. The uptake of telepresence robots to enhance virtual transnational education could lead to a larger international learner population, better virtual transnational education, and more university revenue. Recommendations for future research are also presented. Supplementary Information The online version contains supplementary material available at 10.1186/s40561-021-00173-8.
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