Frontiers in Neurorobotics最新文献_第8页

Rail surface defect data enhancement method based on improved ACGAN 基于改进 ACGAN 的铁路表面缺陷数据增强方法

IF 3.1 4区计算机科学

Frontiers in Neurorobotics Pub Date : 2024-04-09 DOI: 10.3389/fnbot.2024.1397369

He Zhendong, Gao Xiangyang, Liu Zhiyuan, An Xiaoyu, Zheng Anping

引用次数: 0

Extended residual learning with one-shot imitation learning for robotic assembly in semi-structured environment 针对半结构化环境中机器人装配的一次模仿学习与扩展残差学习

IF 3.1 4区计算机科学

Frontiers in Neurorobotics Pub Date : 2024-04-08 DOI: 10.3389/fnbot.2024.1355170

Chuang Wang, Chupeng Su, Baozheng Sun, Gang Chen, Longhan Xie

{"title":"Extended residual learning with one-shot imitation learning for robotic assembly in semi-structured environment","authors":"Chuang Wang, Chupeng Su, Baozheng Sun, Gang Chen, Longhan Xie","doi":"10.3389/fnbot.2024.1355170","DOIUrl":"https://doi.org/10.3389/fnbot.2024.1355170","url":null,"abstract":"IntroductionRobotic assembly tasks require precise manipulation and coordination, often necessitating advanced learning techniques to achieve efficient and effective performance. While residual reinforcement learning with a base policy has shown promise in this domain, existing base policy approaches often rely on hand-designed full-state features and policies or extensive demonstrations, limiting their applicability in semi-structured environments.MethodsIn this study, we propose an innovative Object-Embodiment-Centric Imitation and Residual Reinforcement Learning (OEC-IRRL) approach that leverages an object-embodiment-centric (OEC) task representation to integrate vision models with imitation and residual learning. By utilizing a single demonstration and minimizing interactions with the environment, our method aims to enhance learning efficiency and effectiveness. The proposed method involves three key steps: creating an object-embodiment-centric task representation, employing imitation learning for a base policy using via-point movement primitives for generalization to different settings, and utilizing residual RL for uncertainty-aware policy refinement during the assembly phase.ResultsThrough a series of comprehensive experiments, we investigate the impact of the OEC task representation on base and residual policy learning and demonstrate the effectiveness of the method in semi-structured environments. Our results indicate that the approach, requiring only a single demonstration and less than 1.2 h of interaction, improves success rates by 46% and reduces assembly time by 25%.DiscussionThis research presents a promising avenue for robotic assembly tasks, providing a viable solution without the need for specialized expertise or custom fixtures.","PeriodicalId":12628,"journal":{"name":"Frontiers in Neurorobotics","volume":"36 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2024-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140810365","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}

引用次数: 0

Optimization method for human-robot command combinations of hexapod robot based on multi-objective constraints 基于多目标约束的六足机器人人机指令组合优化方法

IF 3.1 4区计算机科学

Frontiers in Neurorobotics Pub Date : 2024-04-05 DOI: 10.3389/fnbot.2024.1393738

Xiaolei Chen, Bo You, Zheng Dong

{"title":"Optimization method for human-robot command combinations of hexapod robot based on multi-objective constraints","authors":"Xiaolei Chen, Bo You, Zheng Dong","doi":"10.3389/fnbot.2024.1393738","DOIUrl":"https://doi.org/10.3389/fnbot.2024.1393738","url":null,"abstract":"Due to the heavy burden on human drivers when remotely controlling hexapod robots in complex terrain environments, there is a critical need for robot intelligence to assist in generating control commands. Therefore, this study proposes a mapping process framework that generates a combination of human-robot commands based on decision target values, focusing on the task of robot intelligence assisting drivers in generating human-robot command combinations. Furthermore, human-robot state constraints are quantified as geometric constraints on robot motion and driver fatigue constraints. By optimizing and filtering the feasible set of human-robot commands based on human-robot state constraints, instruction combinations are formed and recommended to the driver in real-time, thereby enhancing the efficiency and safety of human-machine coordination. To validate the effectiveness of the proposed method, a remote human-robot collaborative driving control system based on wearable devices is designed and implemented. Experimental results demonstrate that drivers utilizing the human-robot command recommendation system exhibit significantly improved robot walking stability and reduced collision rates compared to individual driving.","PeriodicalId":12628,"journal":{"name":"Frontiers in Neurorobotics","volume":"9 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2024-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140583468","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}

引用次数: 0

The application prospects of robot pose estimation technology: exploring new directions based on YOLOv8-ApexNet 机器人姿态估计技术的应用前景：基于 YOLOv8-ApexNet 的新方向探索

IF 3.1 4区计算机科学

Frontiers in Neurorobotics Pub Date : 2024-04-05 DOI: 10.3389/fnbot.2024.1374385

XianFeng Tang, Shuwei Zhao

{"title":"The application prospects of robot pose estimation technology: exploring new directions based on YOLOv8-ApexNet","authors":"XianFeng Tang, Shuwei Zhao","doi":"10.3389/fnbot.2024.1374385","DOIUrl":"https://doi.org/10.3389/fnbot.2024.1374385","url":null,"abstract":"IntroductionService robot technology is increasingly gaining prominence in the field of artificial intelligence. However, persistent limitations continue to impede its widespread implementation. In this regard, human motion pose estimation emerges as a crucial challenge necessary for enhancing the perceptual and decision-making capacities of service robots.MethodThis paper introduces a groundbreaking model, YOLOv8-ApexNet, which integrates advanced technologies, including Bidirectional Routing Attention (BRA) and Generalized Feature Pyramid Network (GFPN). BRA facilitates the capture of inter-keypoint correlations within dynamic environments by introducing a bidirectional information propagation mechanism. Furthermore, GFPN adeptly extracts and integrates feature information across different scales, enabling the model to make more precise predictions for targets of various sizes and shapes.ResultsEmpirical research findings reveal significant performance enhancements of the YOLOv8-ApexNet model across the COCO and MPII datasets. Compared to existing methodologies, the model demonstrates pronounced advantages in keypoint localization accuracy and robustness.DiscussionThe significance of this research lies in providing an efficient and accurate solution tailored for the realm of service robotics, effectively mitigating the deficiencies inherent in current approaches. By bolstering the accuracy of perception and decision-making, our endeavors unequivocally endorse the widespread integration of service robots within practical applications.","PeriodicalId":12628,"journal":{"name":"Frontiers in Neurorobotics","volume":"2 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2024-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140584727","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}

引用次数: 0

3D human pose data augmentation using Generative Adversarial Networks for robotic-assisted movement quality assessment 利用生成式对抗网络增强三维人体姿态数据，用于机器人辅助运动质量评估

IF 3.1 4区计算机科学

Frontiers in Neurorobotics Pub Date : 2024-04-05 DOI: 10.3389/fnbot.2024.1371385

Xuefeng Wang, Yang Mi, Xiang Zhang

{"title":"3D human pose data augmentation using Generative Adversarial Networks for robotic-assisted movement quality assessment","authors":"Xuefeng Wang, Yang Mi, Xiang Zhang","doi":"10.3389/fnbot.2024.1371385","DOIUrl":"https://doi.org/10.3389/fnbot.2024.1371385","url":null,"abstract":"In the realm of human motion recognition systems, the augmentation of 3D human pose data plays a pivotal role in enriching and enhancing the quality of original datasets through the generation of synthetic data. This augmentation is vital for addressing the current research gaps in diversity and complexity, particularly when dealing with rare or complex human movements. Our study introduces a groundbreaking approach employing Generative Adversarial Networks (GANs), coupled with Support Vector Machine (SVM) and DenseNet, further enhanced by robot-assisted technology to improve the precision and efficiency of data collection. The GANs in our model are responsible for generating highly realistic and diverse 3D human motion data, while SVM aids in the effective classification of this data. DenseNet is utilized for the extraction of key features, facilitating a comprehensive and integrated approach that significantly elevates both the data augmentation process and the model's ability to process and analyze complex human movements. The experimental outcomes underscore our model's exceptional performance in motion quality assessment, showcasing a substantial improvement over traditional methods in terms of classification accuracy and data processing efficiency. These results validate the effectiveness of our integrated network model, setting a solid foundation for future advancements in the field. Our research not only introduces innovative methodologies for 3D human pose data enhancement but also provides substantial technical support for practical applications across various domains, including sports science, rehabilitation medicine, and virtual reality. By combining advanced algorithmic strategies with robotic technologies, our work addresses key challenges in data augmentation and motion quality assessment, paving the way for new research and development opportunities in these critical areas.","PeriodicalId":12628,"journal":{"name":"Frontiers in Neurorobotics","volume":"49 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2024-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140583345","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}

引用次数: 0

Advancing autonomy through lifelong learning: a survey of autonomous intelligent systems 通过终身学习提高自主性：自主智能系统调查

IF 3.1 4区计算机科学

Frontiers in Neurorobotics Pub Date : 2024-04-05 DOI: 10.3389/fnbot.2024.1385778

Dekang Zhu, Qianyi Bu, Zhongpan Zhu, Yujie Zhang, Zhipeng Wang

{"title":"Advancing autonomy through lifelong learning: a survey of autonomous intelligent systems","authors":"Dekang Zhu, Qianyi Bu, Zhongpan Zhu, Yujie Zhang, Zhipeng Wang","doi":"10.3389/fnbot.2024.1385778","DOIUrl":"https://doi.org/10.3389/fnbot.2024.1385778","url":null,"abstract":"The combination of lifelong learning algorithms with autonomous intelligent systems (AIS) is gaining popularity due to its ability to enhance AIS performance, but the existing summaries in related fields are insufficient. Therefore, it is necessary to systematically analyze the research on lifelong learning algorithms with autonomous intelligent systems, aiming to gain a better understanding of the current progress in this field. This paper presents a thorough review and analysis of the relevant work on the integration of lifelong learning algorithms and autonomous intelligent systems. Specifically, we investigate the diverse applications of lifelong learning algorithms in AIS’s domains such as autonomous driving, anomaly detection, robots, and emergency management, while assessing their impact on enhancing AIS performance and reliability. The challenging problems encountered in lifelong learning for AIS are summarized based on a profound understanding in literature review. The advanced and innovative development of lifelong learning algorithms for autonomous intelligent systems are discussed for offering valuable insights and guidance to researchers in this rapidly evolving field.","PeriodicalId":12628,"journal":{"name":"Frontiers in Neurorobotics","volume":"18 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2024-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140583646","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}

引用次数: 0

Designing for usability: development and evaluation of a portable minimally-actuated haptic hand and forearm trainer for unsupervised stroke rehabilitation 可用性设计：开发和评估用于无监督中风康复的便携式微动触觉手部和前臂训练器

IF 3.1 4区计算机科学

Frontiers in Neurorobotics Pub Date : 2024-04-04 DOI: 10.3389/fnbot.2024.1351700

Raphael Rätz, Alexandre L. Ratschat, Nerea Cividanes-Garcia, Gerard M. Ribbers, Laura Marchal-Crespo

{"title":"Designing for usability: development and evaluation of a portable minimally-actuated haptic hand and forearm trainer for unsupervised stroke rehabilitation","authors":"Raphael Rätz, Alexandre L. Ratschat, Nerea Cividanes-Garcia, Gerard M. Ribbers, Laura Marchal-Crespo","doi":"10.3389/fnbot.2024.1351700","DOIUrl":"https://doi.org/10.3389/fnbot.2024.1351700","url":null,"abstract":"In stroke rehabilitation, simple robotic devices hold the potential to increase the training dosage in group therapies and to enable continued therapy at home after hospital discharge. However, we identified a lack of portable and cost-effective devices that not only focus on improving motor functions but also address sensory deficits. Thus, we designed a minimally-actuated hand training device that incorporates active grasping movements and passive pronosupination, complemented by a rehabilitative game with meaningful haptic feedback. Following a human-centered design approach, we conducted a usability study with 13 healthy participants, including three therapists. In a simulated unsupervised environment, the naive participants had to set up and use the device based on written instructions. Our mixed-methods approach included quantitative data from performance metrics, standardized questionnaires, and eye tracking, alongside qualitative feedback from semi-structured interviews. The study results highlighted the device's overall ease of setup and use, as well as its realistic haptic feedback. The eye-tracking analysis further suggested that participants felt safe during usage. Moreover, the study provided crucial insights for future improvements such as a more intuitive and comfortable wrist fixation, more natural pronosupination movements, and easier-to-follow instructions. Our research underscores the importance of continuous testing in the development process and offers significant contributions to the design of user-friendly, unsupervised neurorehabilitation technologies to improve sensorimotor stroke rehabilitation.","PeriodicalId":12628,"journal":{"name":"Frontiers in Neurorobotics","volume":"47 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2024-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140602043","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}

引用次数: 0

Can lower-limb exoskeletons support sit-to-stand motions in frail elderly without crutches? A study combining optimal control and motion capture 下肢外骨骼能否支持没有拐杖的体弱老人从坐到站的运动？优化控制与运动捕捉相结合的研究

IF 3.1 4区计算机科学

Frontiers in Neurorobotics Pub Date : 2024-04-04 DOI: 10.3389/fnbot.2024.1348029

Jan C. L. Lau, Katja Mombaur

{"title":"Can lower-limb exoskeletons support sit-to-stand motions in frail elderly without crutches? A study combining optimal control and motion capture","authors":"Jan C. L. Lau, Katja Mombaur","doi":"10.3389/fnbot.2024.1348029","DOIUrl":"https://doi.org/10.3389/fnbot.2024.1348029","url":null,"abstract":"With the global geriatric population expected to reach 1.5 billion by 2050, different assistive technologies have been developed to tackle age-associated movement impairments. Lower-limb robotic exoskeletons have the potential to support frail older adults while promoting activities of daily living, but the need for crutches may be challenging for this population. Crutches aid safety and stability, but moving in an exoskeleton with them can be unnatural to human movements, and coordination can be difficult. Frail older adults may not have the sufficient arm strength to use them, or prolonged usage can lead to upper limb joint deterioration. The research presented in this paper makes a contribution to a more detailed study of crutch-less exoskeleton use, analyzing in particular the most challenging motion, sit-to-stand (STS). It combines motion capture and optimal control approaches to evaluate and compare the STS dynamics with the TWIN exoskeleton with and without crutches. The results show trajectories that are significantly faster than the exoskeleton's default trajectory, and identify the motor torques needed for full and partial STS assistance. With the TWIN exoskeleton's existing motors being able to support 112 Nm (hips) and 88 Nm (knees) total, assuming an ideal contribution from the device and user, the older adult would need to contribute a total of 8 Nm (hips) and 50 Nm (knees). For TWIN to provide full STS assistance, it would require new motors that can exert at least 121 Nm (hips) and 140 Nm (knees) total. The presented optimal control approaches can be replicated on other exoskeletons to determine the torques required with their mass distributions. Future improvements are discussed and the results presented lay groundwork for eliminating crutches when moving with an exoskeleton.","PeriodicalId":12628,"journal":{"name":"Frontiers in Neurorobotics","volume":"2 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2024-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140583319","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}

引用次数: 0

Cardioid oscillator-based pattern generator for imitating the time-ratio-asymmetrical behavior of the lower limb exoskeleton 基于心形振荡器的模式发生器，用于模仿下肢外骨骼的时间比率不对称行为

IF 3.1 4区计算机科学

Frontiers in Neurorobotics Pub Date : 2024-03-27 DOI: 10.3389/fnbot.2024.1379906

Qiang Fu, Tianhong Luo, TingQiong Cui, Xiangyu Ma, Shuang Liang, Yi Huang, Shengxue Wang

{"title":"Cardioid oscillator-based pattern generator for imitating the time-ratio-asymmetrical behavior of the lower limb exoskeleton","authors":"Qiang Fu, Tianhong Luo, TingQiong Cui, Xiangyu Ma, Shuang Liang, Yi Huang, Shengxue Wang","doi":"10.3389/fnbot.2024.1379906","DOIUrl":"https://doi.org/10.3389/fnbot.2024.1379906","url":null,"abstract":"IntroductionPeriodicity, self-excitation, and time ratio asymmetry are the fundamental characteristics of the human gait. In order to imitate these mentioned characteristics, a pattern generator with four degrees of freedom is proposed based on cardioid oscillators developed by the authors.MethodThe proposed pattern generator is composed of four coupled cardioid oscillators, which are self-excited and have asymmetric time ratios. These oscillators are connected with other oscillators through coupled factors. The dynamic behaviors of the proposed oscillators, such as phase locking, time ratio, and self-excitation, are analyzed via simulations by employing the harmonic balance method. Moreover, for comparison, the simulated trajectories are compared with the natural joint trajectories measured in experiments.Results and discussionSimulation and experimental results show that the behaviors of the proposed pattern generator are similar to those of the natural lower limb. It means the simulated trajectories from the generator are self-excited without any additional inputs and have asymmetric time ratios. Their phases are locked with others. Moreover, the proposed pattern generator can be applied as the reference model for the lower limb exoskeleton controlling algorithm to produce self-adjusted reference trajectories.","PeriodicalId":12628,"journal":{"name":"Frontiers in Neurorobotics","volume":"33 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2024-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140313497","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}

引用次数: 0

Resolving uncertainty on the fly: modeling adaptive driving behavior as active inference 快速解决不确定性：将自适应驾驶行为建模为主动推理

IF 3.1 4区计算机科学

Frontiers in Neurorobotics Pub Date : 2024-03-21 DOI: 10.3389/fnbot.2024.1341750

Johan Engström, Ran Wei, Anthony D. McDonald, Alfredo Garcia, Matthew O'Kelly, Leif Johnson

{"title":"Resolving uncertainty on the fly: modeling adaptive driving behavior as active inference","authors":"Johan Engström, Ran Wei, Anthony D. McDonald, Alfredo Garcia, Matthew O'Kelly, Leif Johnson","doi":"10.3389/fnbot.2024.1341750","DOIUrl":"https://doi.org/10.3389/fnbot.2024.1341750","url":null,"abstract":"Understanding adaptive human driving behavior, in particular how drivers manage uncertainty, is of key importance for developing simulated human driver models that can be used in the evaluation and development of autonomous vehicles. However, existing traffic psychology models of adaptive driving behavior either lack computational rigor or only address specific scenarios and/or behavioral phenomena. While models developed in the fields of machine learning and robotics can effectively learn adaptive driving behavior from data, due to their black box nature, they offer little or no explanation of the mechanisms underlying the adaptive behavior. Thus, generalizable, interpretable, computational models of adaptive human driving behavior are still rare. This paper proposes such a model based on active inference, a behavioral modeling framework originating in computational neuroscience. The model offers a principled solution to how humans trade progress against caution through policy selection based on the single mandate to minimize expected free energy. This casts goal-seeking and information-seeking (uncertainty-resolving) behavior under a single objective function, allowing the model to seamlessly resolve uncertainty as a means to obtain its goals. We apply the model in two apparently disparate driving scenarios that require managing uncertainty, (1) driving past an occluding object and (2) visual time-sharing between driving and a secondary task, and show how human-like adaptive driving behavior emerges from the single principle of expected free energy minimization.","PeriodicalId":12628,"journal":{"name":"Frontiers in Neurorobotics","volume":"153 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2024-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140199662","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}

引用次数: 0