Robotics and Computer-integrated Manufacturing最新文献_第4页

Robot assistance primitives with force-field guidance for shared task collaboration 为共享任务协作提供力场引导的机器人辅助原语

IF 9.1 1区计算机科学

Robotics and Computer-integrated Manufacturing Pub Date : 2025-05-23 DOI: 10.1016/j.rcim.2025.103061

Sophokles Ktistakis , Lucas Gimeno , Fatima-Zahra Laftissi , Alexis Hoss , Antonio De Donno , Mirko Meboldt

{"title":"Robot assistance primitives with force-field guidance for shared task collaboration","authors":"Sophokles Ktistakis , Lucas Gimeno , Fatima-Zahra Laftissi , Alexis Hoss , Antonio De Donno , Mirko Meboldt","doi":"10.1016/j.rcim.2025.103061","DOIUrl":"10.1016/j.rcim.2025.103061","url":null,"abstract":"<div><div>This paper proposes a novel framework for human-robot collaboration (HRC) that addresses the critical need for robots to effectively collaborate with humans on shared tasks within unstructured and dynamic environments. While prior research focused on safety-related aspects, such as collision avoidance in shared workspaces, the task-oriented aspects of human-robot collaboration remain largely underexplored. To address this gap, our framework introduces Robot Assistance Primitives (RAPs). These low-level robot actions integrate both safety and task-related behaviours, enabling the robot to function as a collaborative \"third hand\", and provide assistance across the full spectrum of both physical and contactless interactions. A key component of our approach is an extension of impedance control with virtual force fields, which unifies task-related interactions and safety-related aspects within a single control scheme. The framework leverages a state-of-the-art visual perception pipeline that constructs and tracks real-time 3D digital representations of the workspace and the human operator. Additionally, an Augmented Reality Head-Mounted Display (AR-HMD) facilitates multimodal task programming through user gaze, gestures, and speech, as well as providing visual feedback to foster trust during interactions. We validate the feasibility of the proposed framework and conduct a user study to further evaluate user interactions in a collaborative soldering and assembly task. This research not only addresses limitations of current HRC frameworks but also paves the way for exploring novel collaborative applications.</div></div>","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"96 ","pages":"Article 103061"},"PeriodicalIF":9.1,"publicationDate":"2025-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144116845","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 collaboration scale: A novel approach for assessing robotic systems collaboration capabilities 协作规模：一种评估机器人系统协作能力的新方法

IF 9.1 1区计算机科学

Robotics and Computer-integrated Manufacturing Pub Date : 2025-05-19 DOI: 10.1016/j.rcim.2025.103062

Federico Barravecchia, Riccardo Gervasi, Luca Mastrogiacomo, Fiorenzo Franceschini

{"title":"The collaboration scale: A novel approach for assessing robotic systems collaboration capabilities","authors":"Federico Barravecchia, Riccardo Gervasi, Luca Mastrogiacomo, Fiorenzo Franceschini","doi":"10.1016/j.rcim.2025.103062","DOIUrl":"10.1016/j.rcim.2025.103062","url":null,"abstract":"<div><div>In the transformative landscape of Industry 4.0 and the impending transition to Industry 5.0, the paradigm of collaborative robotics is emerging as a cornerstone, combining human and robotic distinctive abilities. This intersection is leading to a new era of 'human-centric' manufacturing, where the integration of human with robots is not just an option, but a need. In particular, the shift towards Industry 5.0 highlights the return of the human element to technological processes, emphasising adaptability, customization, and collaboration between humans and machines.</div><div>In this context, this study introduces the <em>Collaboration Scale,</em> a metric designed to evaluate the collaborative capabilities of robotic systems within this human-centred framework. This scale provides clear levels of collaboration across five foundational dimensions: <em>Situation awareness, Adaptivity, Communication, Learning</em>, and <em>Mobility</em>.</div><div>The proposed scale has three objectives: (i) establishing a common language for practitioners and researchers, (ii) promoting innovation and standardisation in collaborative robotics, and (iii) providing a practical tool for assessing and comparing the collaborative capabilities of different systems.</div><div>The framework aims to bridge the gap between current capabilities and future aspirations in robotics, while also promoting a human-centric approach for Industry 5.0.</div></div>","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"96 ","pages":"Article 103062"},"PeriodicalIF":9.1,"publicationDate":"2025-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144084529","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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

Enhancing accuracy in Mobile Manipulators: Challenges, current solutions and future needs 提高移动机械手的准确性：挑战，当前解决方案和未来需求

IF 9.1 1区计算机科学

Robotics and Computer-integrated Manufacturing Pub Date : 2025-05-16 DOI: 10.1016/j.rcim.2025.103041

Naroa Núñez-Calvo , Gorka Sorrosal , Itziar Cabanes , Aitziber Mancisidor , Jorge Rodríguez-Guerra

引用次数: 0

Machine learning and deep learning applications in the automotive manufacturing industry: A systematic literature review and industry insights

IF 9.1 1区计算机科学

Robotics and Computer-integrated Manufacturing Pub Date : 2025-05-13 DOI: 10.1016/j.rcim.2025.103034

Soufiane Douimia , Abdelghani Bekrar , Abdessamad Ait El Cadi , Yassin El Hillali , David Fillon

{"title":"Machine learning and deep learning applications in the automotive manufacturing industry: A systematic literature review and industry insights","authors":"Soufiane Douimia , Abdelghani Bekrar , Abdessamad Ait El Cadi , Yassin El Hillali , David Fillon","doi":"10.1016/j.rcim.2025.103034","DOIUrl":"10.1016/j.rcim.2025.103034","url":null,"abstract":"<div><div>In the context of the automotive manufacturing industry, complexity and the extensive data generated during production pose significant challenges. With ongoing technological advancements, effectively harnessing and analyzing this data has become increasingly critical. Machine learning (ML) and deep learning (DL) have emerged as powerful tools to manage complexity and leverage data for enhanced decision-making and process optimization. This systematic literature review examines the application of ML and DL in automotive manufacturing, focusing on application domains, ML/DL model mapping, current trends, and effective implementation practices. Out of 2786 articles, 257 were analyzed, revealing key research areas: equipment optimization (31%), quality enhancement (26%), supply chain optimization (21%), and production efficiency (17%). Energy management was notably underrepresented (4%), indicating a significant opportunity for advancing energy efficiency and decarbonization efforts. Additionally, the review highlighted significant challenges in data management, including data quality, integration, and interoperability issues, which critically affect the successful deployment of ML and DL technologies. Insights from the review were shared with senior management at Toyota Motor Manufacturing France, aligning closely with their strategic vision for digital transformation. Successful implementation of ML and DL hinges on three essential pillars: standardization of manufacturing processes and data, robust IoT and big data infrastructure, and comprehensive human resource development. Embracing these pillars is crucial to navigating complexity, realizing AI’s full potential, and advancing efficiency, sustainability, and innovation in automotive manufacturing.</div></div>","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"96 ","pages":"Article 103034"},"PeriodicalIF":9.1,"publicationDate":"2025-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143943072","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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

Point-driven toolpath curve and orientation smoothing in robotic belt grinding for turbine blade 汽轮机叶片机器人带磨削中点驱动的刀路曲线及方向平滑

IF 9.1 1区计算机科学

Robotics and Computer-integrated Manufacturing Pub Date : 2025-05-09 DOI: 10.1016/j.rcim.2025.103046

Ziling Wang, Lai Zou, Jiantao Li, Junjie Zhang, Wenxi Wang

{"title":"Point-driven toolpath curve and orientation smoothing in robotic belt grinding for turbine blade","authors":"Ziling Wang, Lai Zou, Jiantao Li, Junjie Zhang, Wenxi Wang","doi":"10.1016/j.rcim.2025.103046","DOIUrl":"10.1016/j.rcim.2025.103046","url":null,"abstract":"<div><div>The presence of noise or other abnormal points in the measured point clouds of the turbine blade can result in local discontinuities of the tool path curves, fitted by the machining path points generated by slicing the measured point cloud. In addition, the fluctuation exists in the tool orientation vectors corresponding to the cutter-contact (CC) points in the toolpath curves. These issues can lead to poor smoothing of robotic motion during the grinding process, thereby affecting the quality of the blade grinding. To overcome the above problems, a novel toolpath smoothing method for the measured point cloud model of the turbine blade is proposed. In this method, the initial path points are firstly generated by slicing point clouds of the turbine blade. Next spline segments replace the abnormal points in the initial path points and obtain the smooth toolpath curves. Then, for the initial tool orientation vectors distributed at the smoothed toolpath curves, an objective function by considering the directional deviation between tool orientation vectors and slicing planes is established to reduce the macro fluctuation of these vectors. Based on this, another objective function is established to filter out micro fluctuation among these vectors by considering the energy model of the motion surface of the grinding tool. The surface contour smoothness of the blade with the proposed method is improved by over 20 % compared to other toolpath planning methods.</div></div>","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"96 ","pages":"Article 103046"},"PeriodicalIF":9.1,"publicationDate":"2025-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143924145","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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

Enhancing trajectory tracking accuracy of industrial robots through temporal–spatial mapping and multi-measurement alignment 通过时空映射和多测量对准提高工业机器人轨迹跟踪精度

IF 9.1 1区计算机科学

Robotics and Computer-integrated Manufacturing Pub Date : 2025-05-08 DOI: 10.1016/j.rcim.2025.103039

Chengzhi Wang , Tianjiao Zheng , Tian Xu , Shize Zhao , Ziyuan Yang , Sikai Zhao , Hegao Cai , Jie Zhao , Yanhe Zhu

{"title":"Enhancing trajectory tracking accuracy of industrial robots through temporal–spatial mapping and multi-measurement alignment","authors":"Chengzhi Wang , Tianjiao Zheng , Tian Xu , Shize Zhao , Ziyuan Yang , Sikai Zhao , Hegao Cai , Jie Zhao , Yanhe Zhu","doi":"10.1016/j.rcim.2025.103039","DOIUrl":"10.1016/j.rcim.2025.103039","url":null,"abstract":"<div><div>Robotic machining and automatic offline programming has been developing rapidly over the last decade, yet the absolute accuracy of industrial robots significantly impacts the processing performance, limiting their application in high-precision manufacturing fields. For dynamic non-contact continuous robotic machining tasks, such as laser cutting, precise trajectory tracking performance is especially critical. In this paper, a parallel tracking error compensation framework is proposed to improve the tracking performance of industrial robots, based on temporal–spatial mapping and multi-measurement alignment (TSM-MMA). Major tracking errors originate from nonlinear motor control lag and non-geometric motion transmission errors. The proposed method incorporates both servomotor encoder feedback and laser tracker measurements, enabling parallel distinction and compensation of these errors across trials. Typical linear and circular trajectories are analyzed using TSM to normalize multi-sensor data. Gaussian process regression (GPR) is employed in the MMA process to model the regularity of repetitive measurements, facilitating targeted error compensation. Physical experiments are conducted with an EFORT ER14-1400 robot and a Leica AT960 laser tracker to validate the effectiveness of the proposed framework.</div></div>","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"96 ","pages":"Article 103039"},"PeriodicalIF":9.1,"publicationDate":"2025-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143916894","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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

A parameter separation-based method for kinematic identification of industrial robots without prior kinematic information 基于参数分离的无先验运动学信息工业机器人运动学辨识方法

IF 9.1 1区计算机科学

Robotics and Computer-integrated Manufacturing Pub Date : 2025-05-08 DOI: 10.1016/j.rcim.2025.103037

Fei Liu, Guanbin Gao, Jing Na, Faxiang Zhang

{"title":"A parameter separation-based method for kinematic identification of industrial robots without prior kinematic information","authors":"Fei Liu, Guanbin Gao, Jing Na, Faxiang Zhang","doi":"10.1016/j.rcim.2025.103037","DOIUrl":"10.1016/j.rcim.2025.103037","url":null,"abstract":"<div><div>Accurate kinematic parameters are crucial for deploying industrial robots in high-precision manufacturing applications, such as machining workpieces. Traditional kinematic identification methods often assume that nominal parameter values are known and used as initial estimates. However, in industrial applications, obtaining such nominal values is challenging due to the limited access to detailed design data and the specialized knowledge required for kinematic modeling. This lack of prior kinematic information poses significant challenges to the accuracy and efficiency of parameter identification. To address these issues, we introduce a variable projection (VP) method that eliminates linear parameters through orthogonal projection, transforming the kinematic parameter identification problem into a nonlinear least squares problem involving only the nonlinear parameters. First, the separable structure of the kinematic model is explicitly derived. Then, a novel approach is proposed to integrate the separation of redundant parameters with the VP method. By focusing solely on non-redundant nonlinear parameters, the proposed method significantly reduces reliance on the accuracy of the initial estimates. Simulations and experiments demonstrate that the proposed method achieves more stable parameter estimates and faster convergence in the absence of prior kinematic information. Furthermore, the identified parameters are successfully applied for error compensation in a robotic machining case, leading to an 80% improvement in machining accuracy.</div></div>","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"96 ","pages":"Article 103037"},"PeriodicalIF":9.1,"publicationDate":"2025-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143924144","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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

Autonomous production unit: An architecture for blockchain-based shared manufacturing 自主生产单元：基于区块链的共享制造架构

IF 9.1 1区计算机科学

Robotics and Computer-integrated Manufacturing Pub Date : 2025-05-07 DOI: 10.1016/j.rcim.2025.103035

Nejc Rožman, Marko Corn, Dominik Kozjek, Rok Vrabič, Primož Podržaj

{"title":"Autonomous production unit: An architecture for blockchain-based shared manufacturing","authors":"Nejc Rožman, Marko Corn, Dominik Kozjek, Rok Vrabič, Primož Podržaj","doi":"10.1016/j.rcim.2025.103035","DOIUrl":"10.1016/j.rcim.2025.103035","url":null,"abstract":"<div><div>Driven by technological advancements and the increasing need for efficiency and customization, the manufacturing industry is shifting towards Shared Manufacturing. This strategy enhances global production flexibility and resource utilization by enabling diverse entities to collaboratively engage in distributed manufacturing activities. Expanded resource sharing across industries and society, along with the redefinition of manufacturing resources as marketable services, creates a complex, interconnected production network that demands autonomous production control for effective and flexible management. This study proposes an architectural design for Autonomous Production Units within a blockchain-based Shared Manufacturing system. The design enhances autonomy, allowing independent management and optimization of manufacturing processes while integrating with the global market. The architecture includes two key decision-making submodules: the Business Decisions Submodule, which handles operational activities and interactions with the blockchain network, and the Manufacturing Decisions Submodule, which oversees physical manufacturing processes. The concept is implemented and tested on a case study, demonstrating the Autonomous Production Unit’s capability to autonomously execute the entire manufacturing process, from negotiation to manufacturing service execution, while also handling malfunctions.</div></div>","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"96 ","pages":"Article 103035"},"PeriodicalIF":9.1,"publicationDate":"2025-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143917307","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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

Edge device deployment for intelligent machine tools: A lightweight and interpretable tool wear monitoring method considering wear behavior 智能机床的边缘设备部署：考虑磨损行为的轻量级和可解释的工具磨损监测方法

IF 9.1 1区计算机科学

Robotics and Computer-integrated Manufacturing Pub Date : 2025-05-06 DOI: 10.1016/j.rcim.2025.103033

Yezhen Peng , Weimin Kang , Fengwen Yu , Zequan Ding , Wenhong Zhou , Jianzhong Fu , Songyu Hu

{"title":"Edge device deployment for intelligent machine tools: A lightweight and interpretable tool wear monitoring method considering wear behavior","authors":"Yezhen Peng , Weimin Kang , Fengwen Yu , Zequan Ding , Wenhong Zhou , Jianzhong Fu , Songyu Hu","doi":"10.1016/j.rcim.2025.103033","DOIUrl":"10.1016/j.rcim.2025.103033","url":null,"abstract":"<div><div>Tool wear condition monitoring is essential for reducing production costs and improving machining precision, serving as a key strategy for achieving machine tool intelligence. However, existing methods often depend on empirically designed complex networks to achieve high recognition accuracy, which results in high computational costs, poor performance during later wear stages, and limited interpretability. To address these challenges, a lightweight and interpretable tool wear recognition method is proposed. The feature self-adaptive reconstruction strategy based on wear behavior improves feature quality, while a nonlinear cumulative wear model provides physics guidance, ensuring the model remains lightweight and interpretable. To improve recognition accuracy and robustness during later wear stages, an adaptive loss adjustment mechanism driven by error uncertainty is proposed. Additionally, the influence of reconstructed features on model output is analyzed using shapley additive explanations (SHAP) values, while dependency graphs explore interactions between features across signals and domains, reinforcing physical interpretability. Results show reconstructed features in the y-direction have the greatest influence on model output during side milling. Time-domain and time-frequency domain features dominate, with frequency-domain features providing complementary information. Experiments show the proposed method reduces RMSE by 4.77 and 6.63, MAE by 2.89 and 5.17, and improves R² by 0.06 and 0.12 compared to models with different loss weights and feature processing methods. Recognition accuracy was further improved during later wear stages, achieving RMSE, MAE, and R² values of 3.58, 2.73, and 0.92, respectively. Moreover, the model uses only four fully connected layers, reducing parameters by over 9.32 times, demonstrating the feasibility of edge deployment.</div></div>","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"95 ","pages":"Article 103033"},"PeriodicalIF":9.1,"publicationDate":"2025-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143906114","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 user experience in industrial human-robot interaction: A comparative analysis of Unimodal and Multimodal interfaces for disassembly tasks 工业人机交互中的用户体验：用于拆卸任务的单模态和多模态界面的比较分析

IF 9.1 1区计算机科学

Robotics and Computer-integrated Manufacturing Pub Date : 2025-05-02 DOI: 10.1016/j.rcim.2025.103045

Ainhoa Apraiz, Ganix Lasa, Maitane Mazmela, Nestor Arana-Arexolaleiba, Íñigo Elguea, Oscar Escallada, Nagore Osa, Amaia Etxabe

{"title":"The user experience in industrial human-robot interaction: A comparative analysis of Unimodal and Multimodal interfaces for disassembly tasks","authors":"Ainhoa Apraiz, Ganix Lasa, Maitane Mazmela, Nestor Arana-Arexolaleiba, Íñigo Elguea, Oscar Escallada, Nagore Osa, Amaia Etxabe","doi":"10.1016/j.rcim.2025.103045","DOIUrl":"10.1016/j.rcim.2025.103045","url":null,"abstract":"<div><div>In the Industry 5.0 context, ensuring effective Human-Robot Interaction (HRI) is key to supporting human involvement in production processes. Interfaces are the foundation of this collaboration and serve as vital communication channels which bridge the gap between users and robotic systems. This study compares unimodal and multimodal interfaces and their impact on user experience (UX) in an HRI context. Unimodal interfaces, while simplifying implementation, may restrict the richness of communication, while multimodal interfaces provide detailed and flexible interaction, enhancing the conveyance of complex information. However, designing effective multimodal interfaces presents challenges due to their inherent complexity in managing multiple modalities. This paper presents an HRI disassembly case study comparing the impact of these interfaces on the UX. A methodological approach was used to monitor operator performance, physiological responses, and perceptual responses. An electroencephalogram was employed to objectively record the operators’ emotional responses of operators without interrupting or hindering the process. Twenty participants (10 men and 10 women) were involved in the study. The results indicate that levels of memorization and mental workload are lower when using the multimodal interface, a finding consistent across men and women. These findings suggest that the multimodal interface is an appropriate choice, not only for reducing memorization and mental workload levels, but also for its inclusive approach. This aligns with the objectives of Industry 5.0, promoting the development of technology that meets diverse user preferences and abilities, thereby ensuring greater accessibility and a more user-centric technological landscape.</div></div>","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"95 ","pages":"Article 103045"},"PeriodicalIF":9.1,"publicationDate":"2025-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143895948","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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