Frontiers in NeuroroboticsPub Date : 2024-02-20eCollection Date: 2024-01-01DOI: 10.3389/fnbot.2024.1370415
Jing Luo, Chao Zeng, Zhenyu Lu, Wen Qi
{"title":"Editorial: Sensing and control for efficient human-robot collaboration.","authors":"Jing Luo, Chao Zeng, Zhenyu Lu, Wen Qi","doi":"10.3389/fnbot.2024.1370415","DOIUrl":"https://doi.org/10.3389/fnbot.2024.1370415","url":null,"abstract":"","PeriodicalId":12628,"journal":{"name":"Frontiers in Neurorobotics","volume":"18 ","pages":"1370415"},"PeriodicalIF":3.1,"publicationDate":"2024-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10912567/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140039113","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Weijun Pan, Jian Zhang, Yumei Zhang, Peiyuan Jiang, Shuai Han
{"title":"Assessment and analysis of accents in air traffic control speech: a fusion of deep learning and information theory","authors":"Weijun Pan, Jian Zhang, Yumei Zhang, Peiyuan Jiang, Shuai Han","doi":"10.3389/fnbot.2024.1360094","DOIUrl":"https://doi.org/10.3389/fnbot.2024.1360094","url":null,"abstract":"<sec><title>Introduction</title><p>Enhancing the generalization and reliability of speech recognition models in the field of air traffic control (ATC) is a challenging task. This is due to the limited storage, difficulty in acquisition, and high labeling costs of ATC speech data, which may result in data sample bias and class imbalance, leading to uncertainty and inaccuracy in speech recognition results. This study investigates a method for assessing the quality of ATC speech based on accents. Different combinations of data quality categories are selected according to the requirements of different model application scenarios to address the aforementioned issues effectively.</p></sec><sec><title>Methods</title><p>The impact of accents on the performance of speech recognition models is analyzed, and a fusion feature phoneme recognition model based on prior text information is constructed to identify phonemes of speech uttered by speakers. This model includes an audio encoding module, a prior text encoding module, a feature fusion module, and fully connected layers. The model takes speech and its corresponding prior text as input and outputs a predicted phoneme sequence of the speech. The model recognizes accented speech as phonemes that do not match the transcribed phoneme sequence of the actual speech text and quantitatively evaluates the accents in ATC communication by calculating the differences between the recognized phoneme sequence and the transcribed phoneme sequence of the actual speech text. Additionally, different levels of accents are input into different types of speech recognition models to analyze and compare the recognition accuracy of the models.</p></sec><sec><title>Result</title><p>Experimental results show that, under the same experimental conditions, the highest impact of different levels of accents on speech recognition accuracy in ATC communication is 26.37%.</p></sec><sec><title>Discussion</title><p>This further demonstrates that accents affect the accuracy of speech recognition models in ATC communication and can be considered as one of the metrics for evaluating the quality of ATC speech.</p></sec>","PeriodicalId":12628,"journal":{"name":"Frontiers in Neurorobotics","volume":"103 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2024-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140037520","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Kristel Marmor, Janika Leoste, Mati Heidmets, Katrin Kangur, Martin Rebane, Jaanus Pöial, Tiina Kasuk
{"title":"Keeping social distance in a classroom while interacting via a telepresence robot: a pilot study","authors":"Kristel Marmor, Janika Leoste, Mati Heidmets, Katrin Kangur, Martin Rebane, Jaanus Pöial, Tiina Kasuk","doi":"10.3389/fnbot.2024.1339000","DOIUrl":"https://doi.org/10.3389/fnbot.2024.1339000","url":null,"abstract":"IntroductionThe use of various telecommunication tools has grown significantly. However, many of these tools (e.g., computer-based teleconferencing) are problematic in relaying non-verbal human communication. Telepresence robots (TPRs) are seen as telecommunication tools that can support non-verbal communication.MethodsIn this paper, we examine the usability of TPRs, and communication distance related behavioral realism in communication situations between physically present persons and a TPR-mediated person. Twenty-four participants, who played out 36 communication situations with TPRs, were observed and interviewed.ResultsThe results indicate that TPR-mediated people, especially women, choose shorter than normal communication distances. The type of the robot did not influence the choice of communication distance. The participants perceived the use of TPRs positively as a feasible telecommunication method.DiscussionWhen introducing TPRs, situations with greater intrapersonal distances require more practice compared to scenarios where a physically present person communicates with a telepresent individual in the audience. In the latter situation, the robot-mediated person could be perceived as “behaviorally realistic” much faster than in vice versa communication situations.","PeriodicalId":12628,"journal":{"name":"Frontiers in Neurorobotics","volume":"38 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2024-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139765131","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Design and assessment of a reconfigurable behavioral assistive robot: a pilot study","authors":"Enming Shi, Wenzhuo Zhi, Wanxin Chen, Yuhang Han, Bi Zhang, Xingang Zhao","doi":"10.3389/fnbot.2024.1332721","DOIUrl":"https://doi.org/10.3389/fnbot.2024.1332721","url":null,"abstract":"IntroductionFor patients with functional motor disorders of the lower limbs due to brain damage or accidental injury, restoring the ability to stand and walk plays an important role in clinical rehabilitation. Lower limb exoskeleton robots generally require patients to convert themselves to a standing position for use, while being a wearable device with limited movement distance.MethodsThis paper proposes a reconfigurable behavioral assistive robot that integrates the functions of an exoskeleton robot and an assistive standing wheelchair through a novel mechanism. The new mechanism is based on a four-bar linkage, and through simple and stable conformal transformations, the robot can switch between exoskeleton state, sit-to-stand support state, and wheelchair state. This enables the robot to achieve the functions of assisted walking, assisted standing up, supported standing and wheelchair mobility, respectively, thereby meeting the daily activity needs of sit-to-stand transitions and gait training. The configuration transformation module controls seamless switching between different configurations through an industrial computer. Experimental protocols have been developed for wearable testing of robotic prototypes not only for healthy subjects but also for simulated hemiplegic patients.ResultsThe experimental results indicate that the gait tracking effect during robot-assisted walking is satisfactory, and there are no sudden speed changes during the assisted standing up process, providing smooth support to the wearer. Meanwhile, the activation of the main force-generating muscles of the legs and the plantar pressure decreases significantly in healthy subjects and simulated hemiplegic patients wearing the robot for assisted walking and assisted standing-up compared to the situation when the robot is not worn.DiscussionThese experimental findings demonstrate that the reconfigurable behavioral assistive robot prototype of this study is effective, reducing the muscular burden on the wearer during walking and standing up, and provide effective support for the subject's body. The experimental results objectively and comprehensively showcase the effectiveness and potential of the reconfigurable behavioral assistive robot in the realms of behavioral assistance and rehabilitation training.","PeriodicalId":12628,"journal":{"name":"Frontiers in Neurorobotics","volume":"5 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2024-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139765042","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Erich Mielke, Eric Townsend, David Wingate, John L. Salmon, Marc D. Killpack
{"title":"Human-robot planar co-manipulation of extended objects: data-driven models and control from human-human dyads","authors":"Erich Mielke, Eric Townsend, David Wingate, John L. Salmon, Marc D. Killpack","doi":"10.3389/fnbot.2024.1291694","DOIUrl":"https://doi.org/10.3389/fnbot.2024.1291694","url":null,"abstract":"Human teams are able to easily perform collaborative manipulation tasks. However, simultaneously manipulating a large extended object for a robot and human is a difficult task due to the inherent ambiguity in the desired motion. Our approach in this paper is to leverage data from human-human dyad experiments to determine motion intent for a physical human-robot co-manipulation task. We do this by showing that the human-human dyad data exhibits distinct torque triggers for a lateral movement. As an alternative intent estimation method, we also develop a deep neural network based on motion data from human-human trials to predict future trajectories based on past object motion. We then show how force and motion data can be used to determine robot control in a human-robot dyad. Finally, we compare human-human dyad performance to the performance of two controllers that we developed for human-robot co-manipulation. We evaluate these controllers in three-degree-of-freedom planar motion where determining if the task involves rotation or translation is ambiguous.","PeriodicalId":12628,"journal":{"name":"Frontiers in Neurorobotics","volume":"95 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2024-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139764918","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Axel von Arnim, Jules Lecomte, Naima Elosegui Borras, Stanisław Woźniak, Angeliki Pantazi
{"title":"Dynamic event-based optical identification and communication","authors":"Axel von Arnim, Jules Lecomte, Naima Elosegui Borras, Stanisław Woźniak, Angeliki Pantazi","doi":"10.3389/fnbot.2024.1290965","DOIUrl":"https://doi.org/10.3389/fnbot.2024.1290965","url":null,"abstract":"Optical identification is often done with spatial or temporal visual pattern recognition and localization. Temporal pattern recognition, depending on the technology, involves a trade-off between communication frequency, range, and accurate tracking. We propose a solution with light-emitting beacons that improves this trade-off by exploiting fast event-based cameras and, for tracking, sparse neuromorphic optical flow computed with spiking neurons. The system is embedded in a simulated drone and evaluated in an asset monitoring use case. It is robust to relative movements and enables simultaneous communication with, and tracking of, multiple moving beacons. Finally, in a hardware lab prototype, we demonstrate for the first time beacon tracking performed simultaneously with state-of-the-art frequency communication in the kHz range.","PeriodicalId":12628,"journal":{"name":"Frontiers in Neurorobotics","volume":"13 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2024-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139764922","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Wenhui Huang, Yunhan Lin, Mingxin Liu, Huasong Min
{"title":"Velocity-aware spatial-temporal attention LSTM model for inverse dynamic model learning of manipulators","authors":"Wenhui Huang, Yunhan Lin, Mingxin Liu, Huasong Min","doi":"10.3389/fnbot.2024.1353879","DOIUrl":"https://doi.org/10.3389/fnbot.2024.1353879","url":null,"abstract":"IntroductionAn accurate inverse dynamics model of manipulators can be effectively learned using neural networks. However, further research is required to investigate the impact of spatiotemporal variations in manipulator motion sequences on network learning. In this work, the Velocity Aware Spatial-Temporal Attention Residual LSTM neural network (VA-STA-ResLSTM) is proposed to learn a more accurate inverse dynamics model, which uses a velocity-aware spatial-temporal attention mechanism to extract dynamic spatiotemporal features selectively from the motion sequence of the serial manipulator.MethodsThe multi-layer perception (MLP) attention mechanism is adopted to capture the correlation between joint position and velocity in the motion sequence, and the state correlation between hidden units in the LSTM network to reduce the weight of invalid features. A velocity-aware state fusion approach of LSTM network hidden units' states is proposed, which utilizes variation in joint velocity to adapt to the temporal characteristics of the manipulator dynamic motion, improving the generalization and accuracy of the neural network.ResultsComparative experiments have been conducted on two open datasets and a self-built dataset. Specifically, the proposed method achieved an average accuracy improvement of 61.88% and 43.93% on the two different open datasets and 71.13% on the self-built dataset compared to the LSTM network. These results demonstrate a significant advancement in accuracy for the proposed method.DiscussionCompared with the state-of-the-art inverse dynamics model learning methods of manipulators, the modeling accuracy of the proposed method in this paper is higher by an average of 10%. Finally, by visualizing attention weights to explain the training procedure, it was found that dynamic modeling only relies on partial features, which is meaningful for future optimization of inverse dynamic model learning methods.","PeriodicalId":12628,"journal":{"name":"Frontiers in Neurorobotics","volume":"23 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2024-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139764990","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Alicia Mora, Adrian Prados, Alberto Mendez, Gonzalo Espinoza, Pavel Gonzalez, Blanca Lopez, Victor Muñoz, Luis Moreno, Santiago Garrido, Ramon Barber
{"title":"ADAM: a robotic companion for enhanced quality of life in aging populations","authors":"Alicia Mora, Adrian Prados, Alberto Mendez, Gonzalo Espinoza, Pavel Gonzalez, Blanca Lopez, Victor Muñoz, Luis Moreno, Santiago Garrido, Ramon Barber","doi":"10.3389/fnbot.2024.1337608","DOIUrl":"https://doi.org/10.3389/fnbot.2024.1337608","url":null,"abstract":"One of the major problems of today's society is the rapid aging of its population. Life expectancy is increasing, but the quality of life is not. Faced with the growing number of people who require cognitive or physical assistance, new technological tools are emerging to help them. In this article, we present the ADAM robot, a new robot designed for domestic physical assistance. It mainly consists of a mobile base, two arms with grippers and vision systems. All this allows the performance of physical tasks that require navigation and manipulation of the environment. Among ADAM's features are its modularity, its adaptability to indoor environments and its versatility to function as an experimental platform and for service applications. In addition, it is designed to work respecting the user's personal space and is collaborative, so it can learn from experiences taught by them. We present the design of the robot as well as examples of use in domestic environments both alone and in collaboration with other domestic platforms, demonstrating its potential.","PeriodicalId":12628,"journal":{"name":"Frontiers in Neurorobotics","volume":"23 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2024-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139764999","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Identifying the characteristics of patients with stroke who have difficulty benefiting from gait training with the hybrid assistive limb: a retrospective cohort study","authors":"Shingo Taki, Takeshi Imura, Tsubasa Mitsutake, Yuji Iwamoto, Ryo Tanaka, Naoki Imada, Hayato Araki, Osamu Araki","doi":"10.3389/fnbot.2024.1336812","DOIUrl":"https://doi.org/10.3389/fnbot.2024.1336812","url":null,"abstract":"Robot-assisted gait training is effective for walking independence in stroke rehabilitation, the hybrid assistive limb (HAL) is an example. However, gait training with HAL may not be effective for everyone, and it is not clear who is not expected to benefit. Therefore, we aimed to identify the characteristics of stroke patients who have difficulty gaining benefits from gait training with HAL. We conducted a single-institutional retrospective cohort study. The participants were 82 stroke patients who had received gait training with HAL during hospitalization. The dependent variable was the functional ambulation category (FAC) that a measure of gait independence in stroke patients, and five independent [age, National Institutes of Health Stroke Scale, Brunnstrom recovery stage (BRS), days from stroke onset, and functional independence measure total score (cognitive items)] variables were selected from previous studies and analyzed by logistic regression analysis. We evaluated the validity of logistic regression analysis by using several indicators, such as the area under the curve (AUC), and a confusion matrix. Age, days from stroke onset to HAL initiation, and BRS were identified as factors that significantly influenced walking independence through gait training with HAL. The AUC was 0.86. Furthermore, after building a confusion matrix, the calculated binary accuracy, sensitivity (recall), and specificity were 0.80, 0.80, and 0.81, respectively, indicated high accuracy. Our findings confirmed that older age, greater degree of paralysis, and delayed initiation of HAL-assisted training after stroke onset were associated with increased likelihood of walking dependence upon hospital discharge.","PeriodicalId":12628,"journal":{"name":"Frontiers in Neurorobotics","volume":"7 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2024-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139764912","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Multimodal audio-visual robot fusing 3D CNN and CRNN for player behavior recognition and prediction in basketball matches","authors":"Haiyan Wang","doi":"10.3389/fnbot.2024.1284175","DOIUrl":"https://doi.org/10.3389/fnbot.2024.1284175","url":null,"abstract":"<sec><title>Introduction</title><p>Intelligent robots play a crucial role in enhancing efficiency, reducing costs, and improving safety in the logistics industry. However, traditional path planning methods often struggle to adapt to dynamic environments, leading to issues such as collisions and conflicts. This study aims to address the challenges of path planning and control for logistics robots in complex environments.</p></sec><sec><title>Methods</title><p>The proposed method integrates information from different perception modalities to achieve more accurate path planning and obstacle avoidance control, thereby enhancing the autonomy and reliability of logistics robots. Firstly, a 3D convolutional neural network (CNN) is employed to learn the feature representation of objects in the environment for object recognition. Next, long short-term memory (LSTM) is used to model spatio-temporal features and predict the behavior and trajectory of dynamic obstacles. This enables the robot to accurately predict the future position of obstacles in complex environments, reducing collision risks. Finally, the Dijkstra algorithm is applied for path planning and control decisions to ensure the robot selects the optimal path in various scenarios.</p></sec><sec><title>Results</title><p>Experimental results demonstrate the effectiveness of the proposed method in terms of path planning accuracy and obstacle avoidance performance. The method outperforms traditional approaches, showing significant improvements in both aspects.</p></sec><sec><title>Discussion</title><p>The intelligent path planning and control scheme presented in this paper enhances the practicality of logistics robots in complex environments, thereby promoting efficiency and safety in the logistics industry.</p></sec>","PeriodicalId":12628,"journal":{"name":"Frontiers in Neurorobotics","volume":"98 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2024-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140045383","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}