Authors:S.M.H. Sadati, S. Elnaz Naghibi, Lyndon da Cruz, Christos Bergeles Abstract: Soft robot’s natural dynamics calls for the development of tailored modeling techniques for control. However, the high-dimensional configuration space of the geometrically exact modeling approaches for soft robots, i.e., Cosserat rod and Finite Element Methods (FEM), has been identified as a key obstacle in controller design. To address this challenge, Reduced Order Modeling (ROM), i.e., the approximation of the full-order models, and Model Order Reduction (MOR), i.e., reducing the state space dimension of a high fidelity FEM-based model, are enjoying extensive research. Although both techniques serve a similar purpose and their terms have been used interchangeably in the literature, they are different in their assumptions and implementation. This review paper provides the first in-depth survey of ROM and MOR techniques in the continuum and soft robotics landscape to aid Soft Robotics researchers in selecting computationally efficient models for their specific tasks. PubDate: 2023-09-15T00:00:00Z
Authors:Karolina Zawieska, Glenda Hannibal Abstract: This paper focuses on the topic of “everyday life” as it is addressed in Human-Robot Interaction (HRI) research. It starts from the argument that while human daily life with social robots has been increasingly discussed and studied in HRI, the concept of everyday life lacks clarity or systematic analysis, and it plays only a secondary role in supporting the study of the key HRI topics. In order to help conceptualise everyday life as a research theme in HRI in its own right, we provide an overview of the Social Science and Humanities (SSH) perspectives on everyday life and lived experiences, particularly in sociology, and identify the key elements that may serve to further develop and empirically study such a concept in HRI. We propose new angles of analysis that may help better explore unique aspects of human engagement with social robots. We look at the everyday not just as a reality as we know it (i.e., the realm of the “ordinary”) but also as the future that we need to envision and strive to materialise (i.e., the transformation that will take place through the “extraordinary” that comes with social robots). Finally, we argue that HRI research would benefit not only from engaging with a systematic conceptualisation but also critique of the contemporary everyday life with social robots. This is how HRI studies could play an important role in challenging the current ways of understanding of what makes different aspects of the human world “natural” and ultimately help bringing a social change towards what we consider a “good life.” PubDate: 2023-09-14T00:00:00Z
Authors:Namnueng Protpagorn, Thilina Dulantha Lalitharatne, Leone Costi, Fumiya Iida Abstract: Abdominal palpation is one of the basic but important physical examination methods used by physicians. Visual, auditory, and haptic feedback from the patients are known to be the main sources of feedback they use in the diagnosis. However, learning to interpret this feedback and making accurate diagnosis require several years of training. Many abdominal palpation training simulators have been proposed to date, but very limited attempts have been reported in integrating vocal pain expressions into physical abdominal palpation simulators. Here, we present a vocal pain expression augmentation for a robopatient. The proposed robopatient is capable of providing real-time facial and vocal pain expressions based on the exerted palpation force and position on the abdominal phantom of the robopatient. A pilot study is conducted to test the proposed system, and we show the potential of integrating vocal pain expressions to the robopatient. The platform has also been tested by two clinical experts with prior experience in abdominal palpation. Their evaluations on functionality and suggestions for improvements are presented. We highlight the advantages of the proposed robopatient with real-time vocal and facial pain expressions as a controllable simulator platform for abdominal palpation training studies. Finally, we discuss the limitations of the proposed approach and suggest several future directions for improvements. PubDate: 2023-09-13T00:00:00Z
Authors:Vahan Babushkin, Haneen Alsuradi, Muhammad Hassan Jamil, Muhamed Osman Al-Khalil, Mohamad Eid Abstract: Introduction: Handwriting is a complex task that requires coordination of motor, sensory, cognitive, memory, and linguistic skills to master. The extent these processes are involved depends on the complexity of the handwriting task. Evaluating the difficulty of a handwriting task is a challenging problem since it relies on subjective judgment of experts.Methods: In this paper, we propose a machine learning approach for evaluating the difficulty level of handwriting tasks. We propose two convolutional neural network (CNN) models for single- and multilabel classification where single-label classification is based on the mean of expert evaluation while the multilabel classification predicts the distribution of experts’ assessment. The models are trained with a dataset containing 117 spatio-temporal features from the stylus and hand kinematics, which are recorded for all letters of the Arabic alphabet.Results: While single- and multilabel classification models achieve decent accuracy (96% and 88% respectively) using all features, the hand kinematics features do not significantly influence the performance of the models.Discussion: The proposed models are capable of extracting meaningful features from the handwriting samples and predicting their difficulty levels accurately. The proposed approach has the potential to be used to personalize handwriting learning tools and provide automatic evaluation of the quality of handwriting. PubDate: 2023-09-13T00:00:00Z
Authors:S. I. Panin, T. V. Nechay, A. V. Sazhin, A. E. Tyagunov, N. A. Shcherbakov, A. V. Bykov, K. Yu Melnikov-Makarchuk, A. G. Yuldashev, A. A. Kuznetsov Abstract: Introduction: Complicated diverticulitis is a common abdominal emergency that often requires a surgical intervention. The systematic review and meta-analysis below compare the benefits and harms of robotic vs. laparoscopic surgery in patients with complicated colonic diverticular disease.Methods: The following databases were searched before 1 March 2023: Cochrane Library, PubMed, Embase, CINAHL, and ClinicalTrials.gov. The internal validity of the selected non-randomized studies was assessed using the ROBINS-I tool. The meta-analysis and trial sequential analysis were performed using RevMan 5.4 (Cochrane Collaboration, London, United Kingdom) and Copenhagen Trial Unit Trial Sequential Analysis (TSA) software (Copenhagen Trial Unit, Center for Clinical Intervention Research, Rigshospitalet, Copenhagen, Denmark), respectively.Results: We found no relevant randomized controlled trials in the searched databases. Therefore, we analyzed 5 non-randomized studies with satisfactory internal validity and similar designs comprising a total of 442 patients (184 (41.6%) robotic and 258 (58.4%) laparoscopic interventions). The analysis revealed that robotic surgery for complicated diverticulitis (CD) took longer than laparoscopy (MD = 42 min; 95% CI: [-16, 101]). No statistically significant differences were detected between the groups regarding intraoperative blood loss (MD = −9 mL; 95% CI: [–26, 8]) and the rate of conversion to open surgery (2.17% or 4/184 for robotic surgery vs. 6.59% or 17/258 for laparoscopy; RR = 0.63; 95% CI: [0.10, 4.00]). The type of surgery did not affect the length of in-hospital stay (MD = 0.18; 95% CI: [–0.60, 0.97]) or the rate of postoperative complications (14.1% or 26/184 for robotic surgery vs. 19.8% or 51/258 for laparoscopy; RR = 0.81; 95% CI: [0.52, 1.26]). No deaths were reported in either group.Discussion: The meta-analysis suggests that robotic surgery is an appropriate option for managing complicated diverticulitis. It is associated with a trend toward a lower rate of conversion to open surgery and fewer postoperative complications; however, this trend does not reach the level of statistical significance. Since no high quality RCTs were available, this meta-analysis isnot able to provide reliable conclusion, but only a remarkable lack of proper evidence supporting robotic technology. The need for further evidence-based trials is important. PubDate: 2023-09-13T00:00:00Z
Authors:Pier Luigi Gentili, Pasquale Stano Abstract: Chemical Artificial Intelligence (CAI) is a brand-new research line that exploits molecular, supramolecular, and systems chemistry in wetware (i.e., in fluid solutions) to imitate some performances of human intelligence and promote unconventional robotics based on molecular assemblies, which act in the microscopic world, otherwise tough to be accessed by humans. It is undoubtedly worth spreading the news that AI researchers can rely on the help of chemists and biotechnologists to reach the ambitious goals of building intelligent systems from scratch. This article reports the first attempt at building a Chemical Artificial Intelligence knowledge map and describes the basic intelligent functions that can be implemented through molecular and supramolecular chemistry. Chemical Artificial Intelligence provides new tools and concepts to mimic human intelligence because it shares, with biological intelligence, the same principles and materials. It enables peculiar dynamics, possibly not accessible in software and hardware domains. Moreover, the development of Chemical Artificial Intelligence will contribute to a deeper understanding of the strict link between intelligence and life, which are two of the most remarkable emergent properties shown by the Complex Systems we call biological organisms. PubDate: 2023-09-08T00:00:00Z
Authors:Eileen Roesler Abstract: Introduction: Utilizing anthropomorphic features in industrial robots is a prevalent strategy aimed at enhancing their perception as collaborative team partners and promoting increased tolerance for failures. Nevertheless, recent research highlights the presence of potential drawbacks associated with this approach. It is still widely unknown, how anthropomorphic framing influences the dynamics of trust especially, in context of different failure experiences.Method: The current laboratory study wanted to close this research gap. To do so, fifty-one participants interacted with a robot that was either anthropomorphically or technically framed. In addition, each robot produced either a comprehensible or an incomprehensible failure.Results: The analysis revealed no differences in general trust towards the technically and anthropomorphically framed robot. Nevertheless, the anthropomorphic robot was perceived as more transparent than the technical robot. Furthermore, the robot’s purpose was perceived as more positive after experiencing a comprehensible failure.Discussion: The perceived higher transparency of anthropomorphically framed robots might be a double-edged sword, as the actual transparency did not differ between both conditions. In general, the results show that it is essential to consider trust multi-dimensionally, as a uni-dimensional approach which is often focused on performance might overshadow important facets of trust like transparency and purpose. PubDate: 2023-09-07T00:00:00Z
Authors:Ainhoa Apraiz, Jose Antonio Mulet Alberola, Ganix Lasa, Maitane Mazmela, Hien Ngoc Nguyen Abstract: Humans and robots will increasingly have to work together in the new industrial context. Therefore, it is necessary to improve the User Experience, Technology Acceptance, and overall wellbeing to achieve a smoother and more satisfying interaction while obtaining the maximum performance possible out of it. For this reason, it is essential to analyze these interactions to enhance User Experience. The heuristic evaluation is an easy-to-use, low-cost method that can be applied at different stages of a design process in an iterative manner. Despite these advantages, there is rarely a list of heuristics in the current literature that evaluates Human-Robot interactions both from a User Experience, Technology Acceptance, and Human-Centered approach. Such an approach should integrate key aspects like safety, trust, and perceived safety, ergonomics and workload, inclusivity, and multimodality, as well as robot characteristics and functionalities. Therefore, a new set of heuristics, namely, the HEUROBOX tool, is presented in this work in the form of the HEUROBOX tool to help practitioners and researchers in the assessment of human-robot systems in industrial environments. The HEUROBOX tool clusters design guidelines and methodologies as a logic list of heuristics for human-robot interaction and comprises four categories: Safety, Ergonomics, Functionality, and Interfaces. They include 84 heuristics in the basic evaluation, while the advanced evaluation lists a total of 228 heuristics in order to adapt the tool to the evaluation of different industrial requirements. Finally, the set of new heuristics has been validated by experts using the System Usability Scale (SUS) questionnaire and the categories has been prioritized in order of their importance in the evaluation of Human-Robot Interaction through the Analytic Hierarchy Process (AHP). PubDate: 2023-08-31T00:00:00Z
Authors:David A. Robb, José Lopes, Muneeb I. Ahmad, Peter E. McKenna, Xingkun Liu, Katrin Lohan, Helen Hastie Abstract: Smart speakers and conversational agents have been accepted into our homes for a number of tasks such as playing music, interfacing with the internet of things, and more recently, general chit-chat. However, they have been less readily accepted in our workplaces. This may be due to data privacy and security concerns that exist with commercially available smart speakers. However, one of the reasons for this may be that a smart speaker is simply too abstract and does not portray the social cues associated with a trustworthy work colleague. Here, we present an in-depth mixed method study, in which we investigate this question of embodiment in a serious task-based work scenario of a first responder team. We explore the concepts of trust, engagement, cognitive load, and human performance using a humanoid head style robot, a commercially available smart speaker, and a specially developed dialogue manager. Studying the effect of embodiment on trust, being a highly subjective and multi-faceted phenomena, is clearly challenging, and our results indicate that potentially, the robot, with its anthropomorphic facial features, expressions, and eye gaze, was trusted more than the smart speaker. In addition, we found that embodying a conversational agent helped increase task engagement and performance compared to the smart speaker. This study indicates that embodiment could potentially be useful for transitioning conversational agents into the workplace, and further in situ, “in the wild” experiments with domain workers could be conducted to confirm this. PubDate: 2023-08-30T00:00:00Z
Authors:Kawinna Nipatphonsakun, Takumi Kawasetsu, Koh Hosoda Abstract: Owing to their complex structural design and control system, musculoskeletal robots struggle to execute complicated tasks such as turning with their limited range of motion. This study investigates the utilization of passive toe joints in the foot slip-turning motion of a musculoskeletal robot to turn on its toes with minimum movements to reach the desired angle while increasing the turning angle and its range of mobility. The different conditions of plantar intrinsic muscles (PIM) were also studied in the experiment to investigate the effect of actively controlling the stiffness of toe joints. The results show that the usage of toe joints reduced frictional torque and improved rotational angle. Meanwhile, the results of the toe-lifting angle show that the usage of PIM could contribute to preventing over-dorsiflexion of toes and possibly improving postural stability. Lastly, the results of ground reaction force show that the foot with different stiffness can affect the curve pattern. These findings contribute to the implementations of biological features and utilize them in bipedal robots to simplify their motions, and improve adaptability, regardless of their complex structure. PubDate: 2023-08-29T00:00:00Z
Authors:Jamie Hathaway, Abdelaziz Shaarawy, Cansu Akdeniz, Ali Aflakian, Rustam Stolkin, Alireza Rastegarpanah Abstract: Disassembly of electric vehicle batteries is a critical stage in recovery, recycling and re-use of high-value battery materials, but is complicated by limited standardisation, design complexity, compounded by uncertainty and safety issues from varying end-of-life condition. Telerobotics presents an avenue for semi-autonomous robotic disassembly that addresses these challenges. However, it is suggested that quality and realism of the user’s haptic interactions with the environment is important for precise, contact-rich and safety-critical tasks. To investigate this proposition, we demonstrate the disassembly of a Nissan Leaf 2011 module stack as a basis for a comparative study between a traditional asymmetric haptic-“cobot” master-slave framework and identical master and slave cobots based on task completion time and success rate metrics. We demonstrate across a range of disassembly tasks a time reduction of 22%–57% is achieved using identical cobots, yet this improvement arises chiefly from an expanded workspace and 1:1 positional mapping, and suffers a 10%–30% reduction in first attempt success rate. For unbolting and grasping, the realism of force feedback was comparatively less important than directional information encoded in the interaction, however, 1:1 force mapping strengthened environmental tactile cues for vacuum pick-and-place and contact cutting tasks. PubDate: 2023-08-29T00:00:00Z
Authors:Franka Nauert, Peter Kampmann Abstract: Underwater infrastructure, such as pipelines, requires regular inspection and maintenance including cleaning, welding of defects and valve-turning or hot-stabbing. At the moment, these tasks are mostly performed by divers and Remotely Operated Vehicles (ROVs) but the use of intervention Autonomous Underwater Vehicles (intervention-AUVs) can greatly reduce operation time, risk, and cost. However, autonomous underwater manipulation has not yet reached a high technological readiness and is an intensively researched topic. This review identifies key requirements based on necessary inspection and maintenance methods, linking them to the current technology and deriving major challenges which need to be addressed in development. These include the handling of tools, where a separation between handheld and mounted tools is detected in already employed underwater intervention vehicles such as the Sabertooth by Saab Seaeye or the Aquanaut by Nauticus robotics, two vehicles capable of semi-autonomous intervention. The main challenge identified concerns high level autonomy, i.e., the process of decision-making. This process includes detecting the correct point of interest, maximizing the workspace of the manipulator, planning the manipulation considering required forces, and monitoring the progress to allow for corrections and high quality results. In order to overcome these issues, reliable close range sensing and precise end point navigation is needed. By identifying these persisting challenges, the paper provides inspiration for further development directions in the field of autonomous underwater intervention. PubDate: 2023-08-25T00:00:00Z
Authors:Emmanouil Angelidis Abstract: Our understanding of the complex mechanisms that power biological intelligence has been greatly enhanced through the explosive growth of large-scale neuroscience and robotics simulation tools that are used by the research community to perform previously infeasible experiments, such as the simulation of the neocortex’s circuitry. Nevertheless, simulation falls far from being directly applicable to biorobots due to the large discrepancy between the simulated and the real world. A possible solution for this problem is the further enhancement of existing simulation tools for robotics, AI and neuroscience with multi-physics capabilities. Previously infeasible or difficult to simulate scenarios, such as robots swimming on the water surface, interacting with soft materials, walking on granular materials etc., would be rendered possible within a multi-physics simulation environment designed for robotics. In combination with multi-physics simulation, large-scale simulation tools that integrate multiple simulation modules in a closed-loop manner help address fundamental questions around the organization of neural circuits and the interplay between the brain, body and environment. We analyze existing designs for large-scale simulation running on cloud and HPC infrastructure as well as their shortcomings. Based on this analysis we propose a next-gen modular architecture design based on multi-physics engines, that we believe would greatly benefit biorobotics and AI. PubDate: 2023-08-25T00:00:00Z
Authors:Josh Buckley, Nnamdi Chikere, Yasemin Ozkan-Aydin Abstract: A distinctive feature of quadrupeds that is integral to their locomotion is the tail. Tails serve many purposes in biological systems, including propulsion, counterbalance, and stabilization while walking, running, climbing, or jumping. Similarly, tails in legged robots may augment the stability and maneuverability of legged robots by providing an additional point of contact with the ground. However, in the field of terrestrial bio-inspired legged robotics, the tail is often ignored because of the difficulties in design and control. In this study, we test the hypothesis that a variable stiffness robotic tail can improve the performance of a sprawling quadruped robot by enhancing its stability and maneuverability in various environments. In order to validate our hypothesis, we integrated a cable-driven, flexible tail with multiple segments into the underactuated sprawling quadruped robot, where a single servo motor working alongside a reel and cable mechanism regulates the tail’s stiffness. Our results demonstrated that by controlling the stiffness of the tail, the stability of locomotion on rough terrain and the climbing ability of the robot are improved compared to the movement with a rigid tail and no tail. Our findings highlight that constant ground support provided by the flexible tail is key to maintaining stable locomotion. This ensured a predictable gait cycle, eliminating unexpected turning and slipping, resulting in an increase in locomotion speed and efficiency. Additionally, we observed the robot’s enhanced climbing ability on surfaces inclined up to 20°. The flexibility of the tail enabled the robot to overcome obstacles without external sensing, exhibiting significant adaptability across various terrains. PubDate: 2023-08-24T00:00:00Z
Authors:Federico Allione, Juan D. Gamba, Antonios E. Gkikakis, Roy Featherstone, Darwin Caldwell Abstract: Inertial Measurement Units are present in several applications in aerospace, unmanned vehicle navigation, legged robots, and human motion tracking systems, due to their ability to estimate a body’s acceleration, orientation and angular rate. In contrast to rovers and drones, legged locomotion involves repeated impacts between the feet and the ground, and rapid locomotion (e.g., running) involves alternating stance and flight phases, resulting in substantial oscillations in vertical acceleration. The aim of this research is to investigate the effects of periodic low-acceleration impacts (4 g, 8 g and 16 g), which imitate the vertical motion of a running robot, on the attitude estimation of multiple Micro-Electromechanical Systems IMUs. The results reveal the presence of a significant drift in the attitude estimation of the sensors, which can provide important information during the design process of a robot (sensor selection), or during the control phase (e.g., the system will know that after a series of impacts the attitude estimations will be inaccurate). PubDate: 2023-08-23T00:00:00Z
Authors:Carolina Centeio Jorge, Nikki H. Bouman, Catholijn M. Jonker, Myrthe L. Tielman Abstract: Introduction: Collaboration in teams composed of both humans and automation has an interdependent nature, which demands calibrated trust among all the team members. For building suitable autonomous teammates, we need to study how trust and trustworthiness function in such teams. In particular, automation occasionally fails to do its job, which leads to a decrease in a human’s trust. Research has found interesting effects of such a reduction of trust on the human’s trustworthiness, i.e., human characteristics that make them more or less reliable. This paper investigates how automation failure in a human-automation collaborative scenario affects the human’s trust in the automation, as well as a human’s trustworthiness towards the automation.Methods: We present a 2 × 2 mixed design experiment in which the participants perform a simulated task in a 2D grid-world, collaborating with an automation in a “moving-out” scenario. During the experiment, we measure the participants’ trustworthiness, trust, and liking regarding the automation, both subjectively and objectively.Results: Our results show that automation failure negatively affects the human’s trustworthiness, as well as their trust in and liking of the automation.Discussion: Learning the effects of automation failure in trust and trustworthiness can contribute to a better understanding of the nature and dynamics of trust in these teams and improving human-automation teamwork. PubDate: 2023-08-23T00:00:00Z
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