Frontiers in Robotics and AI最新文献

{"title":"Development of automatic insect-tracking robot system for measuring local activity changes in free walking.","authors":"Ryoko Sekiwa, Tatsuya Ibuki, Shunsuke Shigaki","doi":"10.3389/frobt.2025.1602867","DOIUrl":"10.3389/frobt.2025.1602867","url":null,"abstract":"<p><p>This study aims to develop a robotic system that autonomously tracks insects during free walking to elucidate the relationship between olfactory sensory stimuli and behavioral changes in insects. The adaptability of organisms is defined by their ability to select appropriate behaviors based on sensory inputs in response to environmental changes, a capacity that insects exhibit through efficient adaptive behaviors despite their limited nervous systems. Consequently, new measurement techniques are needed to investigate the neuroethological processes in insects. Traditional behavioral observations of insects have been conducted using free-walking experiments and treadmill techniques; however, these methods face limitations in accurately measuring sensory stimuli and analyzing the factors contributing to detailed behavioral changes. In this study, a robotic system is employed to track free-walking insects while simultaneously recording electroantennogram (EAG) responses at the location of the antenna of the insect during movement, thus enabling the measurement of the relationship between olfactory reception and behavioral change. In this research, we focus on a male silk moth <math><mrow><mo>(</mo> <mrow><mi>B</mi> <mi>o</mi> <mi>m</mi> <mi>b</mi> <mi>y</mi> <mi>x</mi> <mspace></mspace> <mi>m</mi> <mi>o</mi> <mi>r</mi> <mi>i</mi></mrow> <mo>)</mo></mrow> </math> as the target insect and measure its odor source localization behavior. The system comprises a high-speed camera to estimate the movement direction of the insect, a drive system, and instrumentation amplifiers to measure physiological responses. The robot tracks the insect with an error margin of less than 5 mm, recording the EAG responses associated with the olfactory reception during this process. An analysis of the relationship between EAG responses and behavior revealed that the silk moth exhibits a significant amplitude in its EAG responses during the initial odor source localization stage. This suggests that the moth does not necessarily move toward the strongest odor. Further information-theoretic analysis revealed that the moth might be moving in the direction most likely to lead to odor detection, depending on the timing of its olfactory reception. This approach allows for a more natural measurement of the connection between olfactory sensory stimuli and behavior during odor source localization. The study findings are expected to deepen our understanding of the adaptive behaviors of insects.</p>","PeriodicalId":47597,"journal":{"name":"Frontiers in Robotics and AI","volume":"12 ","pages":"1602867"},"PeriodicalIF":2.9,"publicationDate":"2025-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12171283/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144318373","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":"Human interactions with delivery drones in public spaces: design recommendations from recipient and bystander perspectives.","authors":"Shiva Nischal Lingam, Rutger Verstegen, Sebastiaan M Petermeijer, Marieke Martens","doi":"10.3389/frobt.2025.1580289","DOIUrl":"10.3389/frobt.2025.1580289","url":null,"abstract":"<p><p>Drones will likely deliver packages in public spaces, where humans interact as recipients of the package and as bystanders passing by. Understanding the human needs and uncertainties that may arise during these interactions is crucial to ensure safety. This user-centered design study employed twelve interviews and four focus groups to identify key requirements for recipients and bystanders interacting with delivery drones in public spaces. Findings demonstrate different information needs and preferred interface modalities between recipients and bystanders across various interaction stages, from ordering a package to the drone's retraction after delivery. This paper highlights essential design features and offers concrete design recommendations based on the interaction requirements. These recommendations can inform the standardization and customization of design features for each interaction stage, enhancing safety and facilitating natural human-drone interaction. Future research should build on these recommendations and validate the design concepts through experimental user studies involving human interactions with delivery drones in public spaces.</p>","PeriodicalId":47597,"journal":{"name":"Frontiers in Robotics and AI","volume":"12 ","pages":"1580289"},"PeriodicalIF":2.9,"publicationDate":"2025-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12162322/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144303305","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":"\"All things equal\": ethical principles governing why autonomous vehicle experts change or retain their opinions in trolley problems-a qualitative study.","authors":"Stephen R Milford, B Zara Malgir, Bernice S Elger, David M Shaw","doi":"10.3389/frobt.2025.1544272","DOIUrl":"10.3389/frobt.2025.1544272","url":null,"abstract":"<p><strong>Introduction: </strong>Autonomous vehicles (AVs) are already being featured on some public roads. However, there is evidence suggesting that the general public remains particularly concerned and skeptical regarding the ethics of collision scenarios.</p><p><strong>Methods: </strong>This study presents the findings of the first qualitative research into the ethical opinions of experts responsible for the design, deployment, and regulation of AVs. A total of 46 experts were interviewed in this study and presented with two trolley-problem-like vignettes. The experts were asked for an initial opinion on the basis of which the parameters of the vignettes were changed to gauge the principles that would result in either changing or retaining an ethical opinion. Much research has been conducted on public opinion, but there are no available research findings on the ethical opinions of AV experts.</p><p><strong>Results: </strong>Following reflective thematic analysis, four important findings were deduced: 1) although the expert opinions are broadly utilitarian, they are nuanced in significant ways to focus on the impacts of collision scenarios on the community as a whole. 2) Obeying the rules of the road remains a significantly strong ethical opinion. 3) Responsibility and risk play important roles in how AVs should handle collision situations. 4) Egoistic opinions were present to a limited extent.</p><p><strong>Discussion: </strong>The findings show that the ethics of AVs still pose a serious challenge; furthermore, while utilitarianism appears to be a driving ethical principle on the surface, along with the need for both AVs and vulnerable road users to obey the rules, questions concerning community impacts and risk vs. responsibility remain strong influences among AV experts.</p>","PeriodicalId":47597,"journal":{"name":"Frontiers in Robotics and AI","volume":"12 ","pages":"1544272"},"PeriodicalIF":2.9,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12148897/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144267629","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":"From text to motion: grounding GPT-4 in a humanoid robot \"Alter3\".","authors":"Takahide Yoshida, Atsushi Masumori, Takashi Ikegami","doi":"10.3389/frobt.2025.1581110","DOIUrl":"10.3389/frobt.2025.1581110","url":null,"abstract":"<p><p>This paper introduces Alter3, a humanoid robot that demonstrates spontaneous motion generation through the integration of GPT-4, a cutting-edge Large Language Model (LLM). This integration overcomes the challenge of applying LLMs to direct robot control, which typically struggles with the hardware-specific nuances of robotic operation. By translating linguistic descriptions of human actions into robotic movements via programming, Alter3 can autonomously perform a diverse range of actions, such as adopting a \"selfie\" pose or simulating a \"ghost.\" This approach not only shows Alter3's few-shot learning capabilities but also its adaptability to verbal feedback for pose adjustments without manual fine-tuning. This research advances the field of humanoid robotics by bridging linguistic concepts with physical embodiment and opens new avenues for exploring spontaneity in humanoid robots.</p>","PeriodicalId":47597,"journal":{"name":"Frontiers in Robotics and AI","volume":"12 ","pages":"1581110"},"PeriodicalIF":2.9,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12149125/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144267630","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":"Self-assessment in machines boosts human Trust.","authors":"Dana Warmsley, Krishna Choudhary, Jocelyn Rego, Emma Viani, Praveen K Pilly","doi":"10.3389/frobt.2025.1557075","DOIUrl":"10.3389/frobt.2025.1557075","url":null,"abstract":"<p><p>Low trust in autonomous systems remains a significant barrier to adoption and performance. To effectively increase trust in these systems, machines must perform actions to calibrate human trust based on an accurate assessment of both their capability and human trust in real time. Existing efforts demonstrate the value of trust calibration in improving team performance but overlook the importance of machine self-assessment capabilities in the trust calibration process. In our work, we develop a closed-loop trust calibration system for a human-machine collaboration task to classify images and demonstrate about 40% improvement in human trust and 5% improvement in team performance with trained machine self-assessment compared to the baseline, despite the same machine performance level between them. Our trust calibration system applies to any semi-autonomous application requiring human-machine collaboration.</p>","PeriodicalId":47597,"journal":{"name":"Frontiers in Robotics and AI","volume":"12 ","pages":"1557075"},"PeriodicalIF":2.9,"publicationDate":"2025-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12146354/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144259120","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":"A review of robotic and automated systems in meat processing.","authors":"Yining Lyu, Fan Wu, Qingyu Wang, Guanyu Liu, Yingqi Zhang, Huanyu Jiang, Mingchuan Zhou","doi":"10.3389/frobt.2025.1578318","DOIUrl":"10.3389/frobt.2025.1578318","url":null,"abstract":"<p><p>Tasks in the meat processing sector are physically challenging, repetitive, and prone to worker scarcity. Therefore, the imperative adoption of mechanization and automation within the domain of meat processing is underscored by its key role in mitigating labor-intensive processes while concurrently enhancing productivity, safety, and operator wellbeing. This review paper gives an overview of the current research for robotic and automated systems in meat processing. The modules of a robotic system are introduced and afterward, the robotic tasks are divided into three sections with the features of processing targets including livestock, poultry, and seafood. Furthermore, we analyze the technical details of whole meat processing, including skinning, gutting, abdomen cutting, and half-carcass cutting, and discuss these systems in performance and industrial feasibility. The review also refers to some commercialized products for automation in the meat processing industry. Finally, we conclude the review and discuss potential challenges for further robotization and automation in meat processing.</p>","PeriodicalId":47597,"journal":{"name":"Frontiers in Robotics and AI","volume":"12 ","pages":"1578318"},"PeriodicalIF":2.9,"publicationDate":"2025-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12141337/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144250298","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":"Neurotechnology for enhancing human operation of robotic and semi-autonomous systems.","authors":"William J Tyler, Anusha Adavikottu, Christian Lopez Blanco, Archana Mysore, Christopher Blais, Marco Santello, Avinash Unnikrishnan","doi":"10.3389/frobt.2025.1491494","DOIUrl":"10.3389/frobt.2025.1491494","url":null,"abstract":"<p><p>Human operators of remote and semi-autonomous systems must have a high level of executive function to safely and efficiently conduct operations. These operators face unique cognitive challenges when monitoring and controlling robotic machines, such as vehicles, drones, and construction equipment. The development of safe and experienced human operators of remote machines requires structured training and credentialing programs. This review critically evaluates the potential for incorporating neurotechnology into remote systems operator training and work to enhance human-machine interactions, performance, and safety. Recent evidence demonstrating that different noninvasive neuromodulation and neurofeedback methods can improve critical executive functions such as attention, learning, memory, and cognitive control is reviewed. We further describe how these approaches can be used to improve training outcomes, as well as teleoperator vigilance and decision-making. We also describe how neuromodulation can help remote operators during complex or high-risk tasks by mitigating impulsive decision-making and cognitive errors. While our review advocates for incorporating neurotechnology into remote operator training programs, continued research is required to evaluate the how these approaches will impact industrial safety and workforce readiness.</p>","PeriodicalId":47597,"journal":{"name":"Frontiers in Robotics and AI","volume":"12 ","pages":"1491494"},"PeriodicalIF":2.9,"publicationDate":"2025-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12141011/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144250299","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":"Co-design methodology for rapid prototyping of modular robots in care settings.","authors":"Alexandre Colle, Karen Donaldson, Mauro Dragone","doi":"10.3389/frobt.2025.1581506","DOIUrl":"10.3389/frobt.2025.1581506","url":null,"abstract":"<p><strong>Introduction: </strong>This paper introduces a structured co-design methodology for developing modular robotic solutions for the care sector. Despite the widespread adoption of co-design in robotics, existing frameworks often lack clear and systematic processes to effectively incorporate user requirements into tangible robotic designs.</p><p><strong>Method: </strong>To address this gap, the present work proposes an iterative, modular co-design methodology that captures, organises, and translates user insights into practical robotic modules. The methodology employs Design Research (DR) methods combined with Design for Additive Manufacturing (DfAM) principles, enabling rapid prototyping and iterative refinement based on continuous user feedback. The proposed approach was applied in the development of Robobrico, a modular robot created collaboratively with care home users.</p><p><strong>Results: </strong>Outcomes from this study demonstrate that this structured process effectively aligns robot functionality with user expectations, enhances adaptability, and facilitates practical integration of modular robotic platforms in real-world care environments.</p><p><strong>Discussion: </strong>This paper details the proposed methodology, the tools developed to support it, and key insights derived from its implementation.</p>","PeriodicalId":47597,"journal":{"name":"Frontiers in Robotics and AI","volume":"12 ","pages":"1581506"},"PeriodicalIF":2.9,"publicationDate":"2025-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12137090/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144235567","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":"How multimodal narrative and visual representations of human-like service robots shape attitudes and social connection.","authors":"Neil Anthony Daruwala","doi":"10.3389/frobt.2025.1568146","DOIUrl":"10.3389/frobt.2025.1568146","url":null,"abstract":"<p><strong>Introduction: </strong>Public attitudes toward service robots are critical to their acceptance across various industries. Previous research suggests that human-like features and behaviours perceived as empathetic may reduce negative perceptions and enhance emotional engagement. However, there is limited empirical evidence on how structured multimodal interventions influence these responses.</p><p><strong>Methods: </strong>A partially mixed experimental design was employed, featuring one between-subjects factor (group: experimental vs. control) and one within-subjects factor (time: pre-intervention vs. post-intervention), applied only to the experimental group. Two hundred twenty-eight adults (aged 18-65) were randomly assigned to either the experimental or control condition. The intervention included images, video demonstrations of human-like service robots performing socially meaningful gestures, and a narrative vignette depicting human-robot interaction. The control group completed the same assessment measures without the intervention. Outcomes included negative attitudes toward robots (Negative Attitudes Toward Robots Scale, NARS), affect (Positive and Negative Affect Schedule, PANAS), and perceived interpersonal connection (Inclusion of Other in the Self scale, IOS).</p><p><strong>Results: </strong>The experimental group demonstrated a significant reduction in negative attitudes (p < 0.001, Cohen's d = 0.37), as well as lower negative affect and a greater perceived interpersonal connection with the robots (both p < 0.001). Age moderated baseline attitudes, with younger participants reporting more positive initial views; gender was not a significant factor.</p><p><strong>Discussion: </strong>These findings suggest that multimodal portrayals of human-like service robots can improve attitudes, affective responses, and interpersonal connection, offering practical insights for robot design, marketing, and public engagement strategies.</p>","PeriodicalId":47597,"journal":{"name":"Frontiers in Robotics and AI","volume":"12 ","pages":"1568146"},"PeriodicalIF":2.9,"publicationDate":"2025-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12137300/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144235568","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":"Learning to suppress tremors: a deep reinforcement learning-enabled soft exoskeleton for Parkinson's patients.","authors":"Tamás Endrei, Sándor Földi, Ádám Makk, György Cserey","doi":"10.3389/frobt.2025.1537470","DOIUrl":"10.3389/frobt.2025.1537470","url":null,"abstract":"<p><strong>Introduction: </strong>Neurological tremors, prevalent among a large population, are one of the most rampant movement disorders. Biomechanical loading and exoskeletons show promise in enhancing patient well-being, but traditional control algorithms limit their efficacy in dynamic movements and personalized interventions. Furthermore, a pressing need exists for more comprehensive and robust validation methods to ensure the effectiveness and generalizability of proposed solutions.</p><p><strong>Methods: </strong>This paper proposes a physical simulation approach modeling multiple arm joints and tremor propagation. This study also introduces a novel adaptable reinforcement learning environment tailored for disorders with tremors. We present a deep reinforcement learning-based encoder-actor controller for Parkinson's tremors in various shoulder and elbow joint axes displayed in dynamic movements.</p><p><strong>Results: </strong>Our findings suggest that such a control strategy offers a viable solution for tremor suppression in real-world scenarios.</p><p><strong>Discussion: </strong>By overcoming the limitations of traditional control algorithms, this work takes a new step in adapting biomechanical loading into the everyday life of patients. This work also opens avenues for more adaptive and personalized interventions in managing movement disorders.</p>","PeriodicalId":47597,"journal":{"name":"Frontiers in Robotics and AI","volume":"12 ","pages":"1537470"},"PeriodicalIF":2.9,"publicationDate":"2025-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12133501/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144227231","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}