Frontiers in Robotics and AI最新文献

{"title":"Synthetic consciousness architecture.","authors":"Konstantyn Spasokukotskiy","doi":"10.3389/frobt.2024.1437496","DOIUrl":"10.3389/frobt.2024.1437496","url":null,"abstract":"<p><p>This paper presents a theoretical inquiry into the domain of secure artificial superintelligence (ASI). The paper introduces an architectural pattern tailored to fulfill friendly alignment criteria. Friendly alignment refers to a failsafe artificial intelligence alignment that lacks supervision while still having a benign effect on humans. The proposed solution is based on a biomimetic approach to emulate the functional aspects of biological consciousness. It establishes \"morality\" that secures alignment in large systems. The emulated function set is drawn from a cross section of evolutionary and psychiatric frameworks. Furthermore, the paper assesses the architectural potential, practical utility, and limitations of this approach. Notably, the architectural pattern supports straightforward implementation by activating existing foundation models. The models can be underpinned by simple algorithms. Simplicity does not hinder the production of high derivatives, which contribute to alignment strength. The architectural pattern enables the adjustment of alignment strength, enhancing the adaptability and usability of the solution in practical applications.</p>","PeriodicalId":47597,"journal":{"name":"Frontiers in Robotics and AI","volume":"11 ","pages":"1437496"},"PeriodicalIF":2.9,"publicationDate":"2024-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11634756/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142819722","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Motion-generation system for violin-playing robot using reinforcement learning differences in bowing parameters due to changes in learning conditions and sound pressure values.","authors":"Kenzo Horigome, Koji Shibuya","doi":"10.3389/frobt.2024.1439629","DOIUrl":"https://doi.org/10.3389/frobt.2024.1439629","url":null,"abstract":"<p><p>Recently, research on human-robot communication attracts many researchers. We believe that music is one of the important channel between human and robot, because it can convey emotional information. In this research, we focus on the violin performance by a robot. Building a system capable of determining performance from a musical score will leads to better understanding communication through music. In this study, we aim to develop a system that can automatically determine bowing parameters, such as bow speed and bowing direction, from musical scores for a violin-playing robot to produce expressive sounds using reinforcement learning. We adopted Q-learning and ε-greedy methods. In addition, we utilized a neural network to approximate the value function. Our system uses a musical score that incorporates the sound pressure value of each note to determine the bowing speed and direction. This study introduces the design of this system. It also presents simulation results on the differences in bowing parameters caused by changes in learning conditions and sound-pressure values. Regarding learning conditions, the learning rate, discount rate, search rate, and the number of units in the hidden layer in the neural network were changed in the simulation. We used the last two bars of the score and the entire four bars in the first phrase of \"Go Tell Aunt Rhody.\" We determined the number of units in each layer and conducted simulations. Additionally, we conducted an analysis by adjusting the target sound pressure for each note in the score. As a result, negative rewards decreased and positive rewards increased. Consequently, even with changes in target sound pressure in both the last two bars and the entire four bars, the violin-playing robot can automatically play from the score by improving reinforcement learning. It has become clear that achieving an expressive performance using this method is possible.</p>","PeriodicalId":47597,"journal":{"name":"Frontiers in Robotics and AI","volume":"11 ","pages":"1439629"},"PeriodicalIF":2.9,"publicationDate":"2024-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11634750/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142819703","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing interpretability and accuracy of AI models in healthcare: a comprehensive review on challenges and future directions.","authors":"Mohammad Ennab, Hamid Mcheick","doi":"10.3389/frobt.2024.1444763","DOIUrl":"10.3389/frobt.2024.1444763","url":null,"abstract":"<p><p>Artificial Intelligence (AI) has demonstrated exceptional performance in automating critical healthcare tasks, such as diagnostic imaging analysis and predictive modeling, often surpassing human capabilities. The integration of AI in healthcare promises substantial improvements in patient outcomes, including faster diagnosis and personalized treatment plans. However, AI models frequently lack interpretability, leading to significant challenges concerning their performance and generalizability across diverse patient populations. These opaque AI technologies raise serious patient safety concerns, as non-interpretable models can result in improper treatment decisions due to misinterpretations by healthcare providers. Our systematic review explores various AI applications in healthcare, focusing on the critical assessment of model interpretability and accuracy. We identify and elucidate the most significant limitations of current AI systems, such as the black-box nature of deep learning models and the variability in performance across different clinical settings. By addressing these challenges, our objective is to provide healthcare providers with well-informed strategies to develop innovative and safe AI solutions. This review aims to ensure that future AI implementations in healthcare not only enhance performance but also maintain transparency and patient safety.</p>","PeriodicalId":47597,"journal":{"name":"Frontiers in Robotics and AI","volume":"11 ","pages":"1444763"},"PeriodicalIF":2.9,"publicationDate":"2024-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11638409/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142830543","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development of an upper limb passive exosuit for the 2023 ASTM Exo Games.","authors":"Stijn Kindt, Elias Thiery, Stijn Hamelryckx, Adrien Deraes, Tom Verstraten","doi":"10.3389/frobt.2024.1485177","DOIUrl":"10.3389/frobt.2024.1485177","url":null,"abstract":"<p><p>This paper presents the design of the passive upper limb exosuit that won the design competition in the 2023 ASTM Exo Games. The tasks were first analyzed to provide information about the requirements of the design. Then a design was proposed based on the HeroWear Apex exosuit but with improvements from the competition team members. The four tasks of the competition are discussed in detail, including good and poor execution practice. Experiments are performed to measure the forces generated in the elastic elements that support the back and the ones that support the arms. Flex tests are also discussed to show that the exosuit does not hinder the movement of the user in a meaningful way when it is switched off. The performance during the tasks is discussed and based on this and designs of competitors, improvements to the overall design are proposed for future versions.</p>","PeriodicalId":47597,"journal":{"name":"Frontiers in Robotics and AI","volume":"11 ","pages":"1485177"},"PeriodicalIF":2.9,"publicationDate":"2024-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11631734/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142814634","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Editorial: Human-robot collaboration in Industry 5.0: a human-centric AI-based approach.","authors":"Loris Roveda","doi":"10.3389/frobt.2024.1511126","DOIUrl":"https://doi.org/10.3389/frobt.2024.1511126","url":null,"abstract":"","PeriodicalId":47597,"journal":{"name":"Frontiers in Robotics and AI","volume":"11 ","pages":"1511126"},"PeriodicalIF":2.9,"publicationDate":"2024-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11628371/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142807631","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Handle shape influences system usability in telemanipulation.","authors":"Esther I Zoller, Sibylle von Ballmoos, Nicolas Gerig, Philippe C Cattin, Georg Rauter","doi":"10.3389/frobt.2024.1457926","DOIUrl":"10.3389/frobt.2024.1457926","url":null,"abstract":"<p><strong>Introduction: </strong>Ergonomic issues are widespread among surgeons performing teleoperated robotic surgery. As the ergonomics of a teleoperation system depends on the controller handle, it needs to be designed wisely. While the importance of the controller handle in robot-assisted telemanipulation has been highlighted previously, most existing work on the usability of a human-robot system for surgery was of qualitative nature or did not focus on surgery-specific tasks.</p><p><strong>Methods: </strong>We investigated the influence of nine different grasp-type telemanipulator handles on the usability of a lambda.6 haptic input device for a virtual six degrees of freedom peg-in-hole task. User performance with different handles was assessed through four usability metrics: i) task completion time, ii) dimensionless jerk, iii) collision forces, and iv) perceived workload. We compared these usability results with those of a prior study examining only the functional rotational workspace of the same human-robot system.</p><p><strong>Results: </strong>The linear mixed-effect model (LMM) analysis showed that all four usability metrics were dependent on the telemanipulator handle. Moreover, the LMM analysis showed an additional contribution of the hole accessibility to the usability of the human-robot system.</p><p><strong>Discussion: </strong>In case contact forces between the follower end-effector and its surroundings are not critical, the <i>fixed-hook</i>-grasp handle showed the best results out of the nine tested handles. In case low contact forces are crucial, the <i>tripod</i>-grasp handle was most suitable. It can thus be deduced that different grasp-type telemanipulator handles affect system usability for a surgery-related, teleoperated six degrees of freedom placement task. Also, maximizing the functional rotational workspace can positively affect system usability.</p>","PeriodicalId":47597,"journal":{"name":"Frontiers in Robotics and AI","volume":"11 ","pages":"1457926"},"PeriodicalIF":2.9,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11620994/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142802936","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Design of an intelligent wearable device for real-time cattle health monitoring.","authors":"Zhenhua Yu, Yalou Han, Lukas Cha, Shihong Chen, Zeyu Wang, Yang Zhang","doi":"10.3389/frobt.2024.1441960","DOIUrl":"10.3389/frobt.2024.1441960","url":null,"abstract":"<p><p>In the realm of precision cattle health monitoring, this paper introduces the development and evaluation of a novel wearable continuous health monitoring device designed for cattle. The device integrates a sustainable solar-powered module, real-time signal acquisition and processing, and a storage module within an animal ergonomically designed curved casing for non-invasive cattle health monitoring. The curvature of the casing is tailored to better fit the contours of the cattle's neck, significantly enhancing signal accuracy, particularly in temperature signal acquisition. The core module is equipped with precision temperature sensors and inertial measurement units, utilizing the Arduino MKR ZERO board for data acquisition and processing. Field tests conducted on a cohort of ten cattle not only validated the accuracy of temperature sensing but also demonstrated the potential of machine learning, particularly the Support Vector Machine algorithm, for precise behavior classification and step counting, with an average accuracy of 97.27%. This study innovatively combines real-time temperature recognition, behavior classification, and step counting organically within a self-powered device. The results underscore the feasibility of this technology in enhancing cattle welfare and farm management efficiency, providing clear direction for future research to further enhance these devices for large-scale applications.</p>","PeriodicalId":47597,"journal":{"name":"Frontiers in Robotics and AI","volume":"11 ","pages":"1441960"},"PeriodicalIF":2.9,"publicationDate":"2024-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11617366/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142785738","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"On the feasibility of a robotic probe manipulator for echocardiography in the prone position.","authors":"Muhammad Wildan Gifari, Tomoko Machino-Ohtsuka, Takeshi Machino, Modar Hassan, Kenji Suzuki","doi":"10.3389/frobt.2024.1474077","DOIUrl":"https://doi.org/10.3389/frobt.2024.1474077","url":null,"abstract":"<p><p>Robotic probe manipulator for echocardography (echo) can potentially reduce cardiac radiologists' physical burden. Echo procedure with industrial robots has wide Range of Motion (RoM) but poses safety risks because the robot may clamp the patient against the bed. Conversely, a soft robotic manipulator for echo has safe contact force but suffers from a limited RoM. Due to COVID-19, cardiac radiologists explored performing echo in the prone-positioned patients, which yielded good-quality images but was difficult to perform manually. From robot design perspective, prone position allows safer robot without clamping issue because all actuators are under the patient with minimal RoM to reach the cardiac windows. In this work, we propose a robotic probe manipulator for echo in the prone position employing a combination of a delta 3D printer and a soft end-effector and investigate its feasibility in a clinical setting. We implemented the robot as a scanner type device in which the probe manipulator scans from under a bed with an opening around the chest area. The doctor controls the robot with a joystick and a keypad while looking at a camera view of the chest area and the ultrasound display as feedback. For the experiments, three doctors and three medical students scanned the parasternal window of the same healthy subject with the robot and then manually. Two expert cardiologists evaluated the captured ultrasound images. All medical personnel could obtain all the required views with the robot, but the scanning time was considerably longer than the manual one. The ultrasound image quality scores of the doctors' group remained constant between manual and robotic scans. However, the image scores of the robotic scan were lower in the students' group. In summary, this work verified the ability to obtain clinically sufficient images in echocardiography in the prone position by expert medical doctors using the proposed robotic probe manipulator. Our robot can be further developed with semi automatic procedure to serve as a platform for safe and ergonomic echocardiography.</p>","PeriodicalId":47597,"journal":{"name":"Frontiers in Robotics and AI","volume":"11 ","pages":"1474077"},"PeriodicalIF":2.9,"publicationDate":"2024-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11610407/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142773608","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Embodied intelligence for drumming; a reinforcement learning approach to drumming robots.","authors":"Seyed Mojtaba Karbasi, Alexander Refsum Jensenius, Rolf Inge Godøy, Jim Torresen","doi":"10.3389/frobt.2024.1450097","DOIUrl":"https://doi.org/10.3389/frobt.2024.1450097","url":null,"abstract":"<p><p>This paper investigates the potential of the intrinsically motivated reinforcement learning (IMRL) approach for robotic drumming. For this purpose, we implemented an IMRL-based algorithm for a drumming robot called <i>ZRob</i>, an underactuated two-DoF robotic arm with flexible grippers. Two ZRob robots were instructed to play rhythmic patterns derived from MIDI files. The RL algorithm is based on the deep deterministic policy gradient (DDPG) method, but instead of relying solely on extrinsic rewards, the robots are trained using a combination of both extrinsic and intrinsic reward signals. The results of the training experiments show that the utilization of intrinsic reward can lead to meaningful novel rhythmic patterns, while using only extrinsic reward would lead to predictable patterns identical to the MIDI inputs. Additionally, the observed drumming patterns are influenced not only by the learning algorithm but also by the robots' physical dynamics and the drum's constraints. This work suggests new insights into the potential of embodied intelligence for musical performance.</p>","PeriodicalId":47597,"journal":{"name":"Frontiers in Robotics and AI","volume":"11 ","pages":"1450097"},"PeriodicalIF":2.9,"publicationDate":"2024-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11609846/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142773593","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Editorial: Advanced motion control and navigation of robots in extreme environments.","authors":"Allahyar Montazeri, Nargess Sadeghzadeh-Nokhodberiz, Khoshnam Shojaei, Kaspar Althoefer","doi":"10.3389/frobt.2024.1510013","DOIUrl":"https://doi.org/10.3389/frobt.2024.1510013","url":null,"abstract":"","PeriodicalId":47597,"journal":{"name":"Frontiers in Robotics and AI","volume":"11 ","pages":"1510013"},"PeriodicalIF":2.9,"publicationDate":"2024-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11604719/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142773592","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}