Frontiers in Robotics and AI最新文献_第6页

Project-based learning with arduino robots: impact on undergraduate students' achievement and task persistence in robotics programming. 基于项目的arduino机器人学习：对大学生机器人编程成绩和任务持久性的影响

IF 3

Frontiers in Robotics and AI Pub Date : 2025-07-10 eCollection Date: 2025-01-01 DOI: 10.3389/frobt.2025.1615427

Fadip Audu Nannim, Nnenna E Ibezim, Moeketsi Mosia, Basil C E Oguguo

{"title":"Project-based learning with arduino robots: impact on undergraduate students' achievement and task persistence in robotics programming.","authors":"Fadip Audu Nannim, Nnenna E Ibezim, Moeketsi Mosia, Basil C E Oguguo","doi":"10.3389/frobt.2025.1615427","DOIUrl":"10.3389/frobt.2025.1615427","url":null,"abstract":"Introduction: Programming is a fundamental skill in the 21st century, yet there is a global shortage of skilled programmers for high-tech jobs. This study determined the effects of Project-Based Arduino Robot Application (PARA) on undergraduate students' achievement and task persistence in robotics programming.Methods: The quasi-experimental research design was adopted for the study. A sample of 74 second-year computer and robotics education students from three intact classes in three tertiary institutions offering robotics programming II were selected forthe study.Results and discussion: PARA improved the academic achievement of students in robotics programming (63.00 ± 16.81) more than the conventional method, which uses Interactive PowerPoint (IPP) (43.79 ± 12.07). PARA improved the task persistence of students in robotics programming (73.75 ± 13.46) more than the conventional method (40.00 ± 13.70). Male students taught robotics programming using PARA had a slightly higher mean achievement score (69.60 ± 11.50) than their female counterparts (52.00 ± 19.43). Female students taught robotics programming using PARA had a slightly higher mean task persistence score (78.67 ± 11.96) than their male counterparts (70.80 ± 14.02). There was a significant difference (p < 0.05) in students' mean achievement scores based on the instruction method used in teaching robotics programming, among others. These findings have implications for instructing students who find robotics programming difficult and abstract.","PeriodicalId":47597,"journal":{"name":"Frontiers in Robotics and AI","volume":"12 ","pages":"1615427"},"PeriodicalIF":3.0,"publicationDate":"2025-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12286792/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144709442","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

Hybrid disturbance observer and fuzzy logic controller for a new aerial manipulation system. 一种新型航空操纵系统的混合扰动观测器和模糊控制器。

IF 2.9

Frontiers in Robotics and AI Pub Date : 2025-07-07 eCollection Date: 2025-01-01 DOI: 10.3389/frobt.2025.1528415

Alaa Khalifa, Shaaban M Shaaban, Ahmed Khalifa

{"title":"Hybrid disturbance observer and fuzzy logic controller for a new aerial manipulation system.","authors":"Alaa Khalifa, Shaaban M Shaaban, Ahmed Khalifa","doi":"10.3389/frobt.2025.1528415","DOIUrl":"10.3389/frobt.2025.1528415","url":null,"abstract":"Aerial manipulation systems are highly attractive for various applications due to their distinctive features. However, the systems discussed in the literature are constrained by either a restricted number of end-effector degrees of freedom (DOFs) or low payload capability. In our previous research, we mounted a manipulator with a gripper on the underside of a quadrotor to enhance environmental interaction. This paper explores a quadrotor equipped with a 2-DOF manipulator featuring a distinctive topology that allows the end-effector to follow a specified 6-DOF trajectory with the least number of actuators required. An overview of the proposed manipulation system, along with its kinematic and dynamic analysis, is presented. Nevertheless, controlling this system presents significant challenges because of its considerable couplings, nonlinearities, and external disturbances. This paper employs a Disturbance Observer (DOb)-based linearization for an aerial manipulation robot. The DOb-based inner loop is responsible for estimating and compensating nonlinearities and disturbances, which simplifies the control problem into a more straightforward linear control algorithm. Subsequently, a fuzzy logic controller is incorporated into the outer loop to achieve the desired control objectives and closed-loop performance while minimizing computational load. Stability analysis of the proposed controller is introduced. Finally, the system is simulated using MATLAB/SIMULINK, and the results demonstrate tracking accuracy during 6-DOF maneuvers under many kinds of disturbances, with low computational load. The system maintains stability during payload exchanges while respecting all actuator constraints (rotor thrust less than 6 N, joint torques less than 0.7 and 0.4 N.m, respectively). These results demonstrate the effectiveness of the proposed control approach. Also, they show that the proposed controller outperforms the DOb-PD controller's response.","PeriodicalId":47597,"journal":{"name":"Frontiers in Robotics and AI","volume":"12 ","pages":"1528415"},"PeriodicalIF":2.9,"publicationDate":"2025-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12277165/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144683395","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

Rehabilitation robotics and allied digital technologies: opportunities, barriers and solutions for improving their clinical implementation. A position paper from the Fit for Medical Robotics Initiative. 康复机器人和相关数字技术：改善其临床实施的机会、障碍和解决方案。适合医疗机器人计划的立场文件。

IF 2.9

Frontiers in Robotics and AI Pub Date : 2025-07-03 eCollection Date: 2025-01-01 DOI: 10.3389/frobt.2025.1531067

Irene Giovanna Aprile, Silvana Quaglini, Giuseppe Turchetti, Leandro Pecchia, Giovanni Comandè, Furio Gramatica, Emanuele Gruppioni, Giuseppina Sgandurra, Christian Cipriani

{"title":"Rehabilitation robotics and allied digital technologies: opportunities, barriers and solutions for improving their clinical implementation. A position paper from the Fit for Medical Robotics Initiative.","authors":"Irene Giovanna Aprile, Silvana Quaglini, Giuseppe Turchetti, Leandro Pecchia, Giovanni Comandè, Furio Gramatica, Emanuele Gruppioni, Giuseppina Sgandurra, Christian Cipriani","doi":"10.3389/frobt.2025.1531067","DOIUrl":"10.3389/frobt.2025.1531067","url":null,"abstract":"Robotics has been proposed as a promising solution for treating individuals with motor, sensory, and/or cognitive disabilities. Despite the great technological effort put into this field, the translation of robots from the laboratory to the clinical environment is not a seamless and smooth process, and their real-world adoption remains limited. Several barriers to the introduction of robotics in clinical practice have been identified, including a lack of sufficient scientific evidence about its actual cost/effectiveness, resistance to adopting these technologies, and economic, ethical, and regulatory restraints. Fit for Medical Robotics (Fit4MedRob) is an ambitious Initiative designed to bridge the gap between technological innovation and clinical application. One of the main goals of the Initiative is to conduct large-scale pragmatic trials to evaluate the effectiveness and the sustainability of commercially available robotic solutions. To guide the design of these trials, different online surveys have been implemented and delivered to identify the needs of healthcare practitioners and patients at different phases of the disease (acute to chronic) and therapeutic settings (hospital to home care). The results of the Initiative will suggest new organizational models to effectively introduce robotics-assisted rehabilitation into clinical practice. The paper will report on the opportunities of robotics for rehabilitation, the barriers to their clinical implementation, and the proposal of Fit4MedRob to overcome such limitations and facilitate the effective clinical implementation of robotic solutions.","PeriodicalId":47597,"journal":{"name":"Frontiers in Robotics and AI","volume":"12 ","pages":"1531067"},"PeriodicalIF":2.9,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12268264/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144660780","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

Editorial: Bio-inspired legged robotics: design, sensing and control. 编辑：仿生腿机器人：设计、传感和控制。

IF 2.9

Frontiers in Robotics and AI Pub Date : 2025-07-03 eCollection Date: 2025-01-01 DOI: 10.3389/frobt.2025.1600814

Ting Zou

引用次数: 0

Robots for learning: an exploration of teacher roles, perceptions, and challenges in robot-mediated learning. 机器人学习：机器人中介学习中教师角色、认知和挑战的探索。

IF 2.9

Frontiers in Robotics and AI Pub Date : 2025-07-01 eCollection Date: 2025-01-01 DOI: 10.3389/frobt.2025.1441382

Veronica Ahumada-Newhart, Jacquelynne S Eccles

{"title":"Robots for learning: an exploration of teacher roles, perceptions, and challenges in robot-mediated learning.","authors":"Veronica Ahumada-Newhart, Jacquelynne S Eccles","doi":"10.3389/frobt.2025.1441382","DOIUrl":"10.3389/frobt.2025.1441382","url":null,"abstract":"With the increasing popularity of robots for learning, many educational organizations are using telepresence robots for the purpose of remote education. However, as robot-mediated learning is important for the learning experiences of remote and local interactants, it is also important to understand teacher roles and robot design features needed to facilitate these roles in robot-mediated learning experiences. In this paper, we present findings from analysis of a national, multi-case study, where we explore how (N = 60) K-12 teachers perceive their roles in teaching hybrid classrooms where a remote learner used a robot to attend a physical classroom with in-person classmates. This paper presents a qualitative study of the perceived roles for teachers in hybrid classrooms where a remote learner uses a telepresence robot to participate in learning activities. In 46 semi-structured interviews (n = 46) and 6 focus group interviews (n = 2; n = 3; n = 2; n = 3; n = 2; n = 2), coded with a computer assisted qualitative data analysis software (i.e., ATLAS.ti), we captured adapted roles enacted by teachers in robot-mediated learning experiences. First, we present empirical data on educator perceptions of teacher roles as they interact with mobile telepresence robots embodied by remote learners. Specifically, we explore perceptions and roles during in-class learning activities, in-school social activities, and learning preparation activities. Findings from our work will inform novel teacher-centered robot and HRI design that facilitates teaching hybrid classrooms. Findings will also inform future interdisciplinary studies on robot-mediated learning.","PeriodicalId":47597,"journal":{"name":"Frontiers in Robotics and AI","volume":"12 ","pages":"1441382"},"PeriodicalIF":2.9,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12260244/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144643814","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

The impact of intelligent robot service failures on customer responses --a perspective based on mind perception theory. 智能机器人服务失败对顾客反应的影响——基于心理感知理论的视角。

IF 2.9

Frontiers in Robotics and AI Pub Date : 2025-06-30 eCollection Date: 2025-01-01 DOI: 10.3389/frobt.2025.1581083

Mengting Gong, Aimei Li, Junwei Zhang

引用次数: 0

Leveraging learned monocular depth prediction for pose estimation and mapping on unmanned underwater vehicles. 利用学习到的单目深度预测在无人水下航行器上进行姿态估计和映射。

IF 2.9

Frontiers in Robotics and AI Pub Date : 2025-06-26 eCollection Date: 2025-01-01 DOI: 10.3389/frobt.2025.1609765

Marco Job, David Botta, Victor Reijgwart, Luca Ebner, Andrej Studer, Roland Siegwart, Eleni Kelasidi

{"title":"Leveraging learned monocular depth prediction for pose estimation and mapping on unmanned underwater vehicles.","authors":"Marco Job, David Botta, Victor Reijgwart, Luca Ebner, Andrej Studer, Roland Siegwart, Eleni Kelasidi","doi":"10.3389/frobt.2025.1609765","DOIUrl":"https://doi.org/10.3389/frobt.2025.1609765","url":null,"abstract":"This paper presents a general framework that integrates visual and acoustic sensor data to enhance localization and mapping in complex, highly dynamic underwater environments, with a particular focus on fish farming. The pipeline enables net-relative pose estimation for Unmanned Underwater Vehicles (UUVs) and depth prediction within net pens solely from visual data by combining deep learning-based monocular depth prediction with sparse depth priors derived from a classical Fast Fourier Transform (FFT)-based method. We further introduce a method to estimate a UUV's global pose by fusing these net-relative estimates with acoustic measurements, and demonstrate how the predicted depth images can be integrated into the wavemap mapping framework to generate detailed 3D maps in real-time. Extensive evaluations on datasets collected in industrial-scale fish farms confirm that the presented framework can be used to accurately estimate a UUV's net-relative and global position in real-time, and provide 3D maps suitable for autonomous navigation and inspection.","PeriodicalId":47597,"journal":{"name":"Frontiers in Robotics and AI","volume":"12 ","pages":"1609765"},"PeriodicalIF":2.9,"publicationDate":"2025-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12240768/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144609964","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

SuperTac - tactile data super-resolution via dimensionality reduction. SuperTac -通过降维实现触觉数据的超分辨率。

IF 2.9

Frontiers in Robotics and AI Pub Date : 2025-06-26 eCollection Date: 2025-01-01 DOI: 10.3389/frobt.2025.1552922

Neel Patel, Rwik Rana, Deepesh Kumar, Nitish V Thakor

{"title":"SuperTac - tactile data super-resolution via dimensionality reduction.","authors":"Neel Patel, Rwik Rana, Deepesh Kumar, Nitish V Thakor","doi":"10.3389/frobt.2025.1552922","DOIUrl":"10.3389/frobt.2025.1552922","url":null,"abstract":"The advancement of tactile sensing in robotics and prosthetics is constrained by the trade-off between spatial and temporal resolution in artificial tactile sensors. To address this limitation, we propose SuperTac, a novel tactile super-resolution framework that enhances tactile perception beyond the sensor's inherent resolution. Unlike existing approaches, SuperTac combines dimensionality reduction and advanced upsampling to deliver high-resolution tactile information without compromising the performance. Drawing inspiration from the spatiotemporal processing of mechanoreceptors in human tactile systems, SuperTac bridges the gap between sensor limitations and practical applications. In this study, an in-house-built active robotic finger system equipped with a 4 × 4 tactile sensor array was used to palpate textured surfaces. The system, comprising a tactile sensor array mounted on a spring-loaded robotic finger connected to a 3D printer nozzle for precise spatial control, generated spatiotemporal tactile maps. These maps were processed by SuperTac, which integrates a Variational Autoencoder for dimensionality reduction and Residual-In-Residual Blocks (RIRB) for high-quality upsampling. The framework produces super-resolved tactile images (16 × 16), achieving a fourfold improvement in spatial resolution while maintaining computational efficiency for real-time use. Experimental results demonstrate that texture classification accuracy improves by 17% when using super-resolved tactile data compared to raw sensor data. This significant enhancement in classification accuracy highlights the potential of SuperTac for applications in robotic manipulation, object recognition, and haptic exploration. By enabling robots to perceive and interpret high-resolution tactile data, SuperTac marks a step toward bridging the gap between human and robotic tactile capabilities, advancing robotic perception in real-world scenarios.","PeriodicalId":47597,"journal":{"name":"Frontiers in Robotics and AI","volume":"12 ","pages":"1552922"},"PeriodicalIF":2.9,"publicationDate":"2025-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12240741/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144609965","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

Stability and trajectory tracking of four- wheel steering trackless auxiliary transport robot via PID control. 基于PID控制的四轮转向无轨辅助运输机器人的稳定性与轨迹跟踪。

IF 2.9

Frontiers in Robotics and AI Pub Date : 2025-06-25 eCollection Date: 2025-01-01 DOI: 10.3389/frobt.2025.1617376

Mingrui Hao, Yueqi Bi, Jie Ren, Lisen Ma, Jiaran Li, Sihai Zhao, Miao Wu

{"title":"Stability and trajectory tracking of four- wheel steering trackless auxiliary transport robot via PID control.","authors":"Mingrui Hao, Yueqi Bi, Jie Ren, Lisen Ma, Jiaran Li, Sihai Zhao, Miao Wu","doi":"10.3389/frobt.2025.1617376","DOIUrl":"https://doi.org/10.3389/frobt.2025.1617376","url":null,"abstract":"In the complex working environment of underground coal mines, narrow road conditions and deviation in the driving path of autonomous trackless auxiliary transport robots can easily lead to collisions with walls or obstacles. This issue can be effectively solved by a four-wheel steering system, as it can reduce the turning radius of the robot at low speeds and improve its maneuverability at high speeds. Thus, a linear two-degree-of-freedom dynamics model of trackless auxiliary transport robot is established and the steady-state lateral critical speed of 16.6 km/h is obtained. Then a four wheel steering PID trajectory tracking strategy were constructed. Experiments on different steering modes at low and high speeds, which include stepped steering angles and circular path tracking, for the front-wheel steering mode and four-wheel steering mode of the robot are conducted under loaded conditions. The experimental results show that in the low-speed 10 km/h step steering angle input test, compared with the front-wheel steering mode, the turning radius of the robot is reduced by 32.2%, which ensures it easier to pass through narrow tunnels. Under the conditions of a 40 km/h high-speed step steering angle input test, the handling stability has been improved. The results of the circular trajectory tracking test show that at low speeds (10 km/h), the average radius error of the robot is 0.3%, while the radius error of the front-wheel steering robot reaches 2.12%. At high speeds (40 km/h), the average radius error is 2.4%, while the radius error of front-wheel steering mode is 8.74%. The robot maintains good track tracking ability, reducing the risk of collision with tunnel walls and improving robot operation safety.","PeriodicalId":47597,"journal":{"name":"Frontiers in Robotics and AI","volume":"12 ","pages":"1617376"},"PeriodicalIF":2.9,"publicationDate":"2025-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12237676/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144601940","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

A systematic survey: role of deep learning-based image anomaly detection in industrial inspection contexts. 系统综述：基于深度学习的图像异常检测在工业检测中的作用。

IF 2.9

Frontiers in Robotics and AI Pub Date : 2025-06-23 eCollection Date: 2025-01-01 DOI: 10.3389/frobt.2025.1554196

Vinita Shukla, Amit Shukla, Surya Prakash S K, Shraddha Shukla

{"title":"A systematic survey: role of deep learning-based image anomaly detection in industrial inspection contexts.","authors":"Vinita Shukla, Amit Shukla, Surya Prakash S K, Shraddha Shukla","doi":"10.3389/frobt.2025.1554196","DOIUrl":"10.3389/frobt.2025.1554196","url":null,"abstract":"Industrial automation is rapidly evolving, encompassing tasks from initial assembly to final product quality inspection. Accurate anomaly detection is crucial for ensuring the reliability and robustness of automated systems. The intelligence of an industrial automation system is directly linked to its ability to detect and rectify abnormalities, thereby maintaining optimal performance. To advance intelligent manufacturing, sophisticated methods for high-quality process inspection are indispensable. This paper presents a systematic review of existing deep learning methodologies specifically designed for image anomaly detection in the context of industrial manufacturing. Through a comprehensive comparison, traditional techniques are evaluated against state-of-the-art advancements in deep learning-based anomaly detection methodologies, including supervised, unsupervised, and semi-supervised learning methods. Addressing inherent challenges such as real-time processing constraints and imbalanced datasets, this review offers a systematic analysis and mitigation strategies. Additionally, we explore popular anomaly detection datasets for surface defect detection and industrial anomaly detection, along with a critical examination of common evaluation metrics used in image anomaly detection. This review includes an analysis of the performance of current anomaly detection methods on various datasets, elucidating strengths and limitations across different scenarios. Moreover, we delve into the domain of drone-based, manipulator-based and AGV-based anomaly detections using deep learning techniques, highlighting the innovative applications of these methodologies. Lastly, the paper offers scholarly rigor and foresight by addressing emerging challenges and charting a course for future research opportunities, providing valuable insights to researchers in the field of deep learning-based surface defect detection and industrial image anomaly detection.","PeriodicalId":47597,"journal":{"name":"Frontiers in Robotics and AI","volume":"12 ","pages":"1554196"},"PeriodicalIF":2.9,"publicationDate":"2025-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12230580/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144585276","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