Robotics and Computer-integrated Manufacturing最新文献

{"title":"Energy consumption modeling based on operation mechanisms of industrial robots","authors":"Zuoxue Wang, Xiaobin Li, Pei Jiang, Xi Vincent Wang, Haitao Yuan","doi":"10.1016/j.rcim.2025.102971","DOIUrl":"https://doi.org/10.1016/j.rcim.2025.102971","url":null,"abstract":"Industrial robots are widely used in manufacturing industries due to their high efficiency, flexibility, and ability to respond to diverse needs. However, the large-scale deployment of industrial robots has resulted in a significant increase in energy consumption. Therefore, it is crucial to develop an accurate modeling method for predicting the energy consumption of robotic systems, in order to optimize energy usage and achieve green and sustainable development of the manufacturing industry. Based on the analysis of temporal causal relationships between motion variables and the power of industrial robots, as well as spatial dependence between trajectory points, this study proposes a spatial-based torque prediction network and a temporal–spatial-based energy consumption prediction network by combining layer normalization with bidirectional long short-term memory neural network. This model achieves high-precision predictions of robot motion under variable motion modes, time scaling functions, and load conditions. Experimental results with KUKA KR210 and KR60 robots demonstrate that the model achieves the prediction accuracy of 99.01% for joint torque, 96.61% for total power, and 98.72% for total energy consumption under varying conditions.","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"6 1","pages":""},"PeriodicalIF":10.4,"publicationDate":"2025-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143031438","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}

{"title":"Online positioning of thin-walled blade with small curvature for robotic flexible polishing based on optimal local feature matching","authors":"Ruipeng Pan, Zesheng Wang, Hui Wang, Dongbo Wu","doi":"10.1016/j.rcim.2025.102967","DOIUrl":"https://doi.org/10.1016/j.rcim.2025.102967","url":null,"abstract":"The uncertainty of the blade's position and attitude in robotic flexible polishing leads to poor accuracy and stability of force-position coupling, resulting in potential issues like over-polishing or under-polishing, significantly impacting the consistency of final polishing quality. The study proposes an online positioning method of thin-walled blade with small curvature for robotic flexible polishing. The novelty of proposed method lies in that it is based on optimal local geometric feature matching between the actual workpiece and CAD model to obtain the actual position and attitude of thin-walled blade with small curvature and limited measurement area, with a positioning accuracy of 0.3164 mm, thus achieving the adaptive optimization of robotic movement trajectory. Firstly, a mathematical model for the adaptive optimization of robotic movement trajectory based on the actual posture of workpiece is established. The theoretical principles of spatial point cloud mapping based on the forward kinematics model of serial-robot, spatial point cloud registration based on dense and sparse point clouds, workpiece posture analysis based on reverse derivation of point cloud transformation are secondly studied to achieve an accurate positioning of workpiece in the robotic workspace. The error sources of proposed positioning method are analyzed and a quantitative mathematical model is established to characterize the positioning accuracy of workpiece. The feasibility and reliability of proposed positioning method are finally validated through a typical experiment. The results demonstrate that the proposed method can achieve an accurate positioning of thin-walled blade with small curvature and limited measurement area and thereby ensuring the consistency of final polishing quality.","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"85 1","pages":""},"PeriodicalIF":10.4,"publicationDate":"2025-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143031439","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}

{"title":"A generalized generation and evaluation method for cutting process parameter knowledge based on CTGAN","authors":"Dan Li, Tianliang Hu, Lili Dong, Songhua Ma","doi":"10.1016/j.rcim.2025.102963","DOIUrl":"https://doi.org/10.1016/j.rcim.2025.102963","url":null,"abstract":"The machining process knowledge base is a crucial tool in the decision-making process for cutting process parameters, as the diversity and accuracy of its stored process knowledge directly affect the decision effectiveness. To address the complex demands in actual production, it is necessary to adopt effective expansion methods to enrich the process knowledge base content and improve its generalizability. However, current expansion methods face limitations such as insufficient process knowledge coverage and the lack of an effective evaluation mechanism. In response to these issues, this paper proposes a generalized generation and evaluation method for cutting process parameter knowledge based on CTGAN. Firstly, a cutting process data acquisition platform is developed to serve as the basic data source. Then, Conditional Tabular Generative Adversarial Network (CTGAN) is used to construct a generalized generation model to learn the joint distribution law of real process parameter data and enable the intelligent generation of cutting process parameter cases. Finally, the accuracy and applicability of the generated cutting process parameter cases are evaluated through statistical indicator analysis and machine learning performance analysis. The proposed framework is validated using the external cylindrical turning process of a sleeve part as a test case. Results indicate that the generated process parameter data samples not only cover a broader range of machining scenarios but also maintain high quality, which can effectively support the autonomous expansion of machining process knowledge base, and enhance its generalization capability.","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"15 1","pages":""},"PeriodicalIF":10.4,"publicationDate":"2025-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143027342","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}

{"title":"Autonomous path generation for side-seal welding of composite plate billets based on binocular vision and lightweight network VGG16-UNet","authors":"Wanyong Wang, Haohan Sun, Cong Chen, Ke Zhang","doi":"10.1016/j.rcim.2025.102969","DOIUrl":"https://doi.org/10.1016/j.rcim.2025.102969","url":null,"abstract":"For composite plates side-sealing, traditional teaching-playback method is low-quality and inefficient, and cannot adapt to the rapid development of intelligent manufacturing. Aiming at this problem, an autonomous localization and welding path generation method based on binocular vision and lightweight deep learning network is proposed. Firstly, a lightweight background removal model based on VGG16-UNet (Visual Geometry Group Network-16 U-shaped Network) was proposed to eliminate different interference of illumination and redundant information. Secondly, Hough transform with RANSAC (Random Sample Consensus) correction was employed for accurate line extraction from unsharp workpiece edges. Then, an error compensation strategy was presented. Finally, a positioning accuracy of 0.47 mm was achieved, meeting the requirements for side-sealing. Autonomous localization and welding base path generation for composite plate billets with 20 mm depth grooves at a 3000 mm viewing distance were successfully realized. Welding results demonstrate that the proposed method is accurate and reliable, laying a solid foundation for further autonomous pass planning and adaptive controlling.","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"35 1","pages":""},"PeriodicalIF":10.4,"publicationDate":"2025-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143027367","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}

{"title":"Spatial–temporal feature fusion for intelligent foreknowledge of robotic machining errors","authors":"Teng Zhang, Fangyu Peng, Jianzhuang Wang, Zhao Yang, Xiaowei Tang, Rong Yan, Shengqiang Zhao, Runpeng Deng","doi":"10.1016/j.rcim.2025.102972","DOIUrl":"https://doi.org/10.1016/j.rcim.2025.102972","url":null,"abstract":"In recent years, robotic machining has been widely noticed, especially in the manufacturing of large and complex parts, where large workspaces and flexible movements give it an even greater advantage. However, significant intrinsic errors, compliance errors due to weak stiffness of the joints, and spatially dependent nonlinear properties lead to significant challenges in high-precision machining. In this case, the dynamically changing contact area during the material removal process triggers a time-varying cutting force, which in combination with the characteristics of the robot body leads to a typical spatial–temporal coupling process that maps the error onto the workpiece. To address this process, an intelligent foreknowledge method for robot machining error with spatial–temporal feature coupling is proposed by considering the robot ontology error and the machining process. The proposed method carries out joint extraction of robot-related structured features and time-related serialized features and feature-level fusion mapping, respectively, and thus achieves accurate prediction of part machining errors. The proposed method is experimentally validated on eight inner wall workpieces of a cabin segment. Overall, the model achieved an optimal 0.026 mm RMSE on three test sub-workpieces. The ability of the proposed method to accurately extract spatial–temporal features and accurately predict machining errors is also verified through ablation experiments, parameter influence analysis experiments, and intermediate feature analysis. The proposed method takes data-driven as the core idea and spatial–temporal feature extraction as the dual perspective to achieve accurate prediction of robot machining error. It is of great significance for prediction-based accuracy compensation.","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"1 1","pages":""},"PeriodicalIF":10.4,"publicationDate":"2025-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143027363","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}

{"title":"MuViH: Multi-View Hand gesture dataset and recognition pipeline for human–robot interaction in a collaborative robotic finishing platform","authors":"Corentin Hubert, Nathan Odic, Marie Noel, Sidney Gharib, Seyedhossein H.H. Zargarbashi, Lama Séoud","doi":"10.1016/j.rcim.2025.102957","DOIUrl":"https://doi.org/10.1016/j.rcim.2025.102957","url":null,"abstract":"The proliferation of tedious and repetitive tasks on production lines has accelerated the deployment of automated robots. This has also led to a demand for more flexible robots, known as cobots, that can work in collaboration with operators to perform a variety of tasks in different contexts. This paper explores the potential of computer vision-based hand gesture recognition as a means of human–robot interaction within cobotic platforms. Our research focuses on the challenges of gesture recognition in the face of visual occlusions and different camera viewpoints, typical of part finishing tasks in a real-world industrial setting. We introduce a new dataset, MuViH (Multi-View Hand gesture), which features a high variability in camera viewpoints, human operator characteristics, and occlusions, and is fully annotated for hand detection and gesture recognition. We then present a comprehensive hand gesture recognition pipeline that leverages this dataset. Our pipeline incorporates a multi-view aggregation step that significantly enhances gesture recognition accuracy, particularly in the case of visual occlusions. Thanks to extensive experiments and cross-validation on the MuViH dataset and another public dataset, HANDS, our approach demonstrates state-of-the-art performance in gesture recognition. This breakthrough underlines the potential of integrating robust vision-based interaction techniques into cobotic systems, improving flexibility and speed on the production line.","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"6 1","pages":""},"PeriodicalIF":10.4,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143027345","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}

{"title":"A theoretical model to predict performance of integrated robotic systems","authors":"Z.M. Bi, A. Mikkola, H. Handroos, C. Luo","doi":"10.1016/j.rcim.2025.102968","DOIUrl":"https://doi.org/10.1016/j.rcim.2025.102968","url":null,"abstract":"With modularized architecture, integrated solutions can be configured by selecting and assembling a set of selected off-the-shelf functional modules to satisfy users’ needs optimally. While the attributes and properties of these modules are validated at components levels, the performances of system can be affected greatly by integration and interactions. Existing methodologies on system integration focus on system architecture, hardware and software reuses, communications, interfaces, and interoperation. There is the need to develop effective verification and validation (V&V) methods to assure the first-time-right from a virtual model to physical model in terms of the composability of system components to predict the performance of an integrated systems; note that not all attributes of composability can be verified by self-adaptability of cyber-physical systems. In this paper, we will focus on V&V of integrated robotic systems, and we will explore the relations of an integrated system with its components in terms of some performance criteria including functionalities, responsiveness, accuracy, and repeatability. The problem itself is newly formulated, and it is crucial for designers to predict and optimize system performance based on the selection and assemblage of system modules. The work in this paper opens new field of research in standardizing verification and validation process in designing collaborative robot systems","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"87 1","pages":""},"PeriodicalIF":10.4,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143027343","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}

{"title":"A novel dynamic observer-based contact force control strategy in robotic grinding to improve blade profile accuracy","authors":"Yilin Mu, Lai Zou, Ziling Wang, Heng Li, Shengbo Yan, Wenxi Wang","doi":"10.1016/j.rcim.2025.102966","DOIUrl":"https://doi.org/10.1016/j.rcim.2025.102966","url":null,"abstract":"Complex curvature changes and uneven allowance distribution significantly hinder the ability of traditional robotic belt grinding methods to achieve high-precision blade processing. To resolve this problem, a novel dynamic observer-based contact force control strategy is proposed in this paper by considering the dynamic contact force (DCF) model and partitioned force control (PFC) strategy. The DCF model is developed by considering the contact pressure distribution across different blade areas, while the over-grinding depth error is derived by analyzing the contact pressure coupling influenced by row spacing. The CC points with large allowance are divided into regions based on the variation of ideal normal contact force. Then, the reference normal contact force for each region is determined. Moreover, a dynamic observer-based adaptive impedance controller (DO-AIC) is developed to enhance reference normal contact force control. Verification experiment showed that DO-AIC increased force control accuracy by 78.27% compared to without the controller. Furthermore, four sets of robotic grinding experiments on turbine blades were performed to validate the superiority of the proposed method. The results showed that with DO-PFG, the surface profile accuracy at blade four areas improved to 0.244 mm, 0.188 mm, 0.193 mm, and 0.203 mm, representing improvements of 53.7%, 79.57%, 59.37%, and 67.26% compared to TG, respectively.","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"8 1","pages":""},"PeriodicalIF":10.4,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143027344","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}

{"title":"Adaptive safety-critical control using a variable task energy tank for collaborative robot tasks under dynamic environments","authors":"Zhitao Gao, Chen Chen, Fangyu Peng, Yukui Zhang, Haoyan Liu, Wenke Zhou, Rong Yan, Xiaowei Tang","doi":"10.1016/j.rcim.2025.102964","DOIUrl":"https://doi.org/10.1016/j.rcim.2025.102964","url":null,"abstract":"Collaborative robots are widely used in interaction tasks due to their low cost and high operational flexibility. However, compared to industrial robots, they have lower joint stiffness and are more sensitive to external environments, leading to larger motion tracking errors. Therefore, in interaction tasks within complex dynamic environments, such as wiping tasks with unexpected collision disturbances and drilling tasks with material property changes, maintaining the stability of the robot's motion velocity is crucial for improving task performance. To address these concerns, a comprehensive passive safety control framework is proposed in this work. The framework ensures system stability while imposing consistently constraints on non-passive power of the controller, resulting in high performance in the presence of external disturbances and material property changes. This is achieved by combining the Variable Energy Tank with the Adaptive Control Barrier Function method. On this basis, two key parameter design strategies of the framework are proposed, including a variable reference energy boundary strategy and an adaptive conservative factor strategy. The effectiveness of the proposed method is validated by real-world experiments involving wiping and drilling.","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"22 1","pages":""},"PeriodicalIF":10.4,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143027346","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}

{"title":"A human-centric order release method based on workload control in high-variety make-to-order shops towards Industry 5.0","authors":"Lin Ma, Ray Y. Zhong, Mingze Yuan, Kai Ding, Matthias Thürer, Yanghua Pan, Ting Qu, Geroge Q. Huang","doi":"10.1016/j.rcim.2024.102946","DOIUrl":"https://doi.org/10.1016/j.rcim.2024.102946","url":null,"abstract":"Industry 5.0 emphasizes a human-centric concept, aiming to construct highly intelligent, sustainable, and resilient manufacturing systems. While a large body of literature has explored its concepts, architectures, enabling technologies, and practical applications, literature specifically focused on production planning and control solutions in industry 5.0 shops are scarce. Recent literature indicates that the well-being and skills of human workers significantly impact shop performance due to their highly variable activities and behaviors. Workload control has been recognized as a simple yet effective solution to mitigate the effects of high variability - both human and machine - through a three-layer filter for high-variety make-to-order shops, offering potential for Industry 5.0. However, the existing workload control concept has two significant limitations. First, it primarily focuses on the workload of machines while ignoring the potential impacts of humans, and; Second, this concept relied on the fixed processing times and lack flexibility to cope with changes in human subjective behaviors. In response, this study first presents a human-centric order release method based on workload control, enhancing its adaptability by considering uncertain human processing times. Furthermore, we introduce five shop floor priority dispatching rules to further investigate the potential impacts of additional factors on our proposed method. Simulation results show that the human-centric method outperforms the traditional machine-centric method, particularly in pure job shops. Meanwhile, when combining the human-centric order release method with the shop floor dispatching rules, the load-oriented dispatching rules significantly improve the shop's performance in terms of throughput time, while the time-oriented dispatching rules increase order delivery performance. Counterintuitively, integrating human-centric concept into the shop floor dispatching stage is noteworthy, i.e. human-centric shop floor dispatching rule. It does not enhance shop performance compared to the original dispatching rules, but rather deteriorates the performance of order release on most measures. The findings of this study have important implications for both research and practice in Industry 5.0.","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"30 1","pages":""},"PeriodicalIF":10.4,"publicationDate":"2025-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142989081","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}