Frontiers in Robotics and AI最新文献_第2页

Diffusion models for robotic manipulation: a survey. 机器人操作的扩散模型：综述。

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Frontiers in Robotics and AI Pub Date : 2025-09-09 eCollection Date: 2025-01-01 DOI: 10.3389/frobt.2025.1606247

Rosa Wolf, Yitian Shi, Sheng Liu, Rania Rayyes

引用次数: 0

Editorial: Advancements in vibration control for space manipulators: actuators, algorithms, and material innovations. 社论：空间机械臂振动控制的进展：致动器、算法和材料创新。

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Frontiers in Robotics and AI Pub Date : 2025-09-05 eCollection Date: 2025-01-01 DOI: 10.3389/frobt.2025.1681168

Javad Tayebi, Ti Chen, Xiaofeng Wu, Anand Kumar Mishra

引用次数: 0

Combining vision and range sensors for AMCL localization in corridor environments with rectangular signs. 结合视觉和距离传感器的矩形标识走廊环境AMCL定位。

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Frontiers in Robotics and AI Pub Date : 2025-09-05 eCollection Date: 2025-01-01 DOI: 10.3389/frobt.2025.1652251

Paloma de la Puente, Germán Vega-Martínez, Patricia Javierre, Javier Laserna, Elena Martin-Arias

{"title":"Combining vision and range sensors for AMCL localization in corridor environments with rectangular signs.","authors":"Paloma de la Puente, Germán Vega-Martínez, Patricia Javierre, Javier Laserna, Elena Martin-Arias","doi":"10.3389/frobt.2025.1652251","DOIUrl":"10.3389/frobt.2025.1652251","url":null,"abstract":"Localization is widely recognized as a fundamental problem in mobile robotics. Even though robust localization methods do exist for many applications, it is difficult for them to succeed in complex environments and challenging situations. In particular, corridor-like environments present important issues for traditional range-based methods. The main contribution of this paper is the integration of new observation models into the popular AMCL ROS node, considering visual features obtained from the detection of rectangular landmarks. Visual rectangles are distinctive elements which are very common in man-made environments and should be detected and recognized in a robust manner. This hybrid approach is developed and evaluated both for the combination of an omnidirectional camera and a laser sensor (using artificial markers) and for RGB-D sensors (using natural rectangular features). For the latter, this work also introduces RIDGE, a novel algorithm for detecting projected quadrilaterals representing rectangles in images. Simulations and real world experiments are presented for both cases. As shown and discussed in the article, the proposed approach provides significant advantages for specific conditions and common scenarios such as long straight corridors.","PeriodicalId":47597,"journal":{"name":"Frontiers in Robotics and AI","volume":"12 ","pages":"1652251"},"PeriodicalIF":3.0,"publicationDate":"2025-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12447077/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145114438","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}

引用次数: 0

Integrating emotional intelligence, memory architecture, and gestures to achieve empathetic humanoid robot interaction in an educational setting. 整合情商、记忆架构和手势，在教育环境中实现感同身受的类人机器人互动。

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Frontiers in Robotics and AI Pub Date : 2025-09-04 eCollection Date: 2025-01-01 DOI: 10.3389/frobt.2025.1635419

Fuze Sun, Lingyu Li, Shixiangyue Meng, Xiaoming Teng, Terry R Payne, Paul Craig

{"title":"Integrating emotional intelligence, memory architecture, and gestures to achieve empathetic humanoid robot interaction in an educational setting.","authors":"Fuze Sun, Lingyu Li, Shixiangyue Meng, Xiaoming Teng, Terry R Payne, Paul Craig","doi":"10.3389/frobt.2025.1635419","DOIUrl":"10.3389/frobt.2025.1635419","url":null,"abstract":"This study investigates the integration of individual human traits into an empathetically adaptive educational robot tutor system designed to improve student engagement and learning outcomes with corresponding Engagement Vector measurements. While prior research in the field of Human-Robot Interaction (HRI) has examined the integration of the traits, such as emotional intelligence, memory-driven personalization, and non-verbal communication, by themselves, they have thus-far neglected to consider their synchronized integration into a cohesive, operational education framework. To address this gap, we customize a Multi-Modal Large Language Model (Llama 3.2 from Meta) deployed with modules for human-like traits (emotion, memory and gestures) into an AI-Agent framework. This constitutes the robot's intelligent core that mimics the human emotional system, memory architecture and gesture controller to allow the robot to behave more empathetically while recognizing and responding appropriately to the student's emotional state. It can also recall the student's past learning record and adapt its style of interaction accordingly. This allows the robot tutor to react to the student in a more sympathetic manner by delivering personalized verbal feedback synchronized with relevant gestures. Our study suggests the extent of this effect through the introduction of Engagement Vector Model which can be a benchmark for judging the quality of HRI experience. Quantitative and qualitative results demonstrate that such an empathetic responsive approach significantly improves student engagement and learning outcomes compared with a baseline humanoid robot without these human-like traits. This indicates that robot tutors with empathetic capabilities can create a more supportive, interactive learning experience that ultimately leads to better outcomes for the student.","PeriodicalId":47597,"journal":{"name":"Frontiers in Robotics and AI","volume":"12 ","pages":"1635419"},"PeriodicalIF":3.0,"publicationDate":"2025-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12444663/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145114466","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}

引用次数: 0

Integrating large language models for intuitive robot navigation. 集成大型语言模型，实现直观的机器人导航。

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Frontiers in Robotics and AI Pub Date : 2025-09-04 eCollection Date: 2025-01-01 DOI: 10.3389/frobt.2025.1627937

Ziheng Xue, Arturs Elksnis, Ning Wang

引用次数: 0

Editorial: Computer vision mechanisms for resource-constrained robotics applications. 编辑：资源受限机器人应用的计算机视觉机制。

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Frontiers in Robotics and AI Pub Date : 2025-09-02 eCollection Date: 2025-01-01 DOI: 10.3389/frobt.2025.1680098

Rui Pimentel de Figueiredo, Christian Limberg, Lorenzo Jamone, Alexandre Bernardino

引用次数: 0

Editorial: Towards HRI of everyday life. 社论：走向日常生活的HRI。

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Frontiers in Robotics and AI Pub Date : 2025-09-01 eCollection Date: 2025-01-01 DOI: 10.3389/frobt.2025.1657518

Karolina Zawieska, Mohammad Obaid, Wafa Johal

引用次数: 0

EEG-CLIP: learning EEG representations from natural language descriptions. EEG- clip：从自然语言描述中学习EEG表征。

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Frontiers in Robotics and AI Pub Date : 2025-08-26 eCollection Date: 2025-01-01 DOI: 10.3389/frobt.2025.1625731

Tidiane Camaret Ndir, Robin T Schirrmeister, Tonio Ball

{"title":"EEG-CLIP: learning EEG representations from natural language descriptions.","authors":"Tidiane Camaret Ndir, Robin T Schirrmeister, Tonio Ball","doi":"10.3389/frobt.2025.1625731","DOIUrl":"10.3389/frobt.2025.1625731","url":null,"abstract":"Deep networks for electroencephalogram (EEG) decoding are often only trained to solve one specific task, such as pathology or age decoding. A more general task-agnostic approach is to train deep networks to match a (clinical) EEG recording to its corresponding textual medical report and vice versa. This approach was pioneered in the computer vision domain matching images and their text captions and subsequently allowed to do successful zero-shot decoding using textual class prompts. In this work, we follow this approach and develop a contrastive learning framework, EEG-CLIP, that aligns the EEG time series and the descriptions of the corresponding clinical text in a shared embedding space. We investigated its potential for versatile EEG decoding, evaluating performance in a range of few-shot and zero-shot settings. Overall, we show that EEG-CLIP manages to non-trivially align text and EEG representations. Our work presents a promising approach to learn general EEG representations, which could enable easier analyses of diverse decoding questions through zero-shot decoding or training task-specific models from fewer training examples. The code for reproducing our results is available at https://github.com/tidiane-camaret/EEGClip.","PeriodicalId":47597,"journal":{"name":"Frontiers in Robotics and AI","volume":"12 ","pages":"1625731"},"PeriodicalIF":3.0,"publicationDate":"2025-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12417489/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145041848","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}

引用次数: 0

Multimodal perception-driven decision-making for human-robot interaction: a survey. 人机交互中的多模态感知驱动决策研究。

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Frontiers in Robotics and AI Pub Date : 2025-08-22 eCollection Date: 2025-01-01 DOI: 10.3389/frobt.2025.1604472

Wenzheng Zhao, Kruthika Gangaraju, Fengpei Yuan

{"title":"Multimodal perception-driven decision-making for human-robot interaction: a survey.","authors":"Wenzheng Zhao, Kruthika Gangaraju, Fengpei Yuan","doi":"10.3389/frobt.2025.1604472","DOIUrl":"10.3389/frobt.2025.1604472","url":null,"abstract":"Multimodal perception is essential for enabling robots to understand and interact with complex environments and human users by integrating diverse sensory data, such as vision, language, and tactile information. This capability plays a crucial role in decision-making in dynamic, complex environments. This survey provides a comprehensive review of advancements in multimodal perception and its integration with decision-making in robotics from year 2004-2024. We systematically summarize existing multimodal perception-driven decision-making (MPDDM) frameworks, highlighting their advantages in dynamic environments and the methodologies employed in human-robot interaction (HRI). Beyond reviewing these frameworks, we analyze key challenges in multimodal perception and decision-making, focusing on technical integration and sensor noise, adaptation, domain generalization, and safety and robustness. Finally, we outline future research directions, emphasizing the need for adaptive multimodal fusion techniques, more efficient learning paradigms, and human-trusted decision-making frameworks to advance the HRI field.","PeriodicalId":47597,"journal":{"name":"Frontiers in Robotics and AI","volume":"12 ","pages":"1604472"},"PeriodicalIF":3.0,"publicationDate":"2025-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12411148/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145015295","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}

引用次数: 0

Designing for flourishing: a conceptual model for enhancing older adults' well-being with social robots. 为繁荣而设计：一个利用社交机器人提高老年人福祉的概念模型。

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Frontiers in Robotics and AI Pub Date : 2025-08-20 eCollection Date: 2025-01-01 DOI: 10.3389/frobt.2025.1607373

Chantal Klier, Birgit Lugrin

{"title":"Designing for flourishing: a conceptual model for enhancing older adults' well-being with social robots.","authors":"Chantal Klier, Birgit Lugrin","doi":"10.3389/frobt.2025.1607373","DOIUrl":"10.3389/frobt.2025.1607373","url":null,"abstract":"This article gives a new perspective on designing robotic applications in elderly care with a special focus on socially assistive robots and seniors' well-being. While various applications have been proposed there is currently no common conceptual model in designing interventions with social robots for seniors. Therefore, we propose a conceptual model that identifies five key domains for designing applications for socially interactive robots to enhance seniors' well-being. We base our conceptual model on established theories from the social sciences. Namely, we propose that application design should consider integrating Self-Determination Theory by addressing the three basic psychological needs (autonomy, competence, and relatedness) to enhance seniors' wellbeing. Furthermore, we recommend assessing the impact of social robots on well-being using the five building blocks of the PERMA framework: positive emotions, engagement, relationships, meaning, and accomplishment. By integrating these theoretical perspectives, researchers and developers gain a structured approach to designing social robot applications for cognitively healthy older adults and evaluating their effects.","PeriodicalId":47597,"journal":{"name":"Frontiers in Robotics and AI","volume":"12 ","pages":"1607373"},"PeriodicalIF":3.0,"publicationDate":"2025-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12404932/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145001677","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}

引用次数: 0