Robotics and Computer-integrated Manufacturing最新文献

{"title":"A dual knowledge embedded hybrid model based on augmented data and improved loss function for tool wear monitoring","authors":"Xiaohui Fang ,&nbsp;Qinghua Song ,&nbsp;Jing Qin ,&nbsp;Zhenyang Li ,&nbsp;Haifeng Ma ,&nbsp;Zhanqiang Liu","doi":"10.1016/j.rcim.2024.102901","DOIUrl":"10.1016/j.rcim.2024.102901","url":null,"abstract":"<div><div>Tool wear monitoring (TWM) is essential for enhancing the machining accuracy of intelligent manufacturing systems and ensuring the consistency and reliability of products. The complex and dynamic processing environment demands higher real-time monitoring and generalization ability of TWM. Traditional data-driven models lack guided training in physical processes and are limited by the amount of samples with wear labels. To guide the model to capture the underlying physical mechanism and enhance compliance with the law of tool wear, a dual knowledge embedded hybrid model based on augmented data and improved loss function for TWM is proposed in this paper. The second training data source is obtained by constructing the mapping relationship between cutting force and tool wear, which effectively complements and enhances the physical characteristics between the data and addresses the issue of insufficient labeled data in actual network training. Subsequently, a structure integrating serial convolution, parallel convolution, bidirectional gated recurrent unit (BiGRU) and attention mechanism is developed to extract the spatial and temporal features in time series data. Moreover, Based on the physical law of tool wear, an improved loss function with physical constraints is proposed to improve the physical consistency of the model. The experimental results show that the model prediction RMSE error is reduced by 12.67% after augmented data compared to a single data source, and the RMSE error of the prediction result is reduced by 25.16% at most after the improvement of the loss function. The model has high prediction accuracy within short training epochs and good real-time performance. The proposed approach provides a modeling strategy with low computational resource requirements based on the fusion of physical and data information.</div></div>","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"92 ","pages":"Article 102901"},"PeriodicalIF":9.1,"publicationDate":"2024-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142637642","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 real-time collision avoidance method for redundant dual-arm robots in an open operational environment","authors":"Yi Wu ,&nbsp;Xiaohui Jia ,&nbsp;Tiejun Li ,&nbsp;Jinyue Liu","doi":"10.1016/j.rcim.2024.102894","DOIUrl":"10.1016/j.rcim.2024.102894","url":null,"abstract":"<div><div>Due to the structural resemblance of redundant dual-arm robots to human arms, they are widely employed to replace humans in open operational environments. Addressing safety concerns related to the autonomous operations of redundant dual-arm robots in open environments, this paper proposes a real-time collision avoidance method. Firstly, an avoidance direction adjustment algorithm is designed based on the avoidance function method, providing a collision avoidance formulation for the robot control point. Secondly, an obstacle classification algorithm is devised to categorize obstacles into robot body obstacles and end-effector obstacles, and the collision avoidance strategy of redundant dual-arm robots is designed. Subsequently, a collision avoidance penalty factor is introduced based on the proximity between the end-effector and the target point, ensuring the convergence of the joint velocity. Finally, a novel collision avoidance formulation for redundant manipulators is presented, further extended under dual-arm coordinated tasks. Numerical simulations and physical experiments demonstrate that the proposed method can achieve self-collision avoidance for redundant dual-arm robots and dynamic/static obstacle avoidance in dual-arm coordinated tasks, with smooth collision avoidance maneuvers. The research results provide safety guidelines for autonomous operations of redundant dual-arm robots in open operational environments.</div></div>","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"92 ","pages":"Article 102894"},"PeriodicalIF":9.1,"publicationDate":"2024-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142643208","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":"Less gets more attention: A novel human-centered MR remote collaboration assembly method with information recommendation and visual enhancement","authors":"Yuxiang Yan,&nbsp;Xiaoliang Bai,&nbsp;Weiping He,&nbsp;Shuxia Wang,&nbsp;XiangYu Zhang,&nbsp;Liwei Liu,&nbsp;Qing Yu,&nbsp;Bing Zhang","doi":"10.1016/j.rcim.2024.102898","DOIUrl":"10.1016/j.rcim.2024.102898","url":null,"abstract":"<div><div>Mixed reality remote collaboration assembly is a type of computer-supported collaborative assembly work that uses mixed reality technology to enable spatial information and collaboration status sharing among geographically distributed collaborators, including remote experts and local users. However, due to the abundance of mixed virtual and real-world information in the MR space and the limitations imposed by narrow field-of-view augmented reality (AR) glasses, users face challenges in effectively focusing on relevant and valuable visual information. Our research aims to enhance users' visual attention to critical guidance information in MR collaborative assembly tasks, thereby improving the clear expression of instructions and facilitating the transmission of collaborative intention. We developed the Information Recommendation and Visual Enhancement System (IRVES) through an assembly process information hierarchy division mechanism, a content-based information recommendation system, and a gesture interaction-based information visual enhancement method. IRVES can leverage the guidance expertise and preferences of remote experts to recommend information to filter out irrelevant information and present the key information that the remote expert conveys to the local user in an intuitive way through visual enhancement. We conducted a user study experiment of a collaborative assembly task of a small engine in a laboratory environment. The experimental results indicate that IRVES outperforms traditional MR remote collaborative assembly methods (VG3DV) in terms of time performance, operational errors, cognitive performance and user experience. Our research contributes a human-centered information visualization approach for remote experts and local users, providing a novel method and idea for designing visual information interfaces in MR remote collaboration assembly tasks.</div></div>","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"92 ","pages":"Article 102898"},"PeriodicalIF":9.1,"publicationDate":"2024-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142637644","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":"Drilling task planning and offline programming of a robotic multi-spindle drilling system for aero-engine nacelle acoustic liners","authors":"Fanqiang Kong ,&nbsp;Biao Mei ,&nbsp;Yun Fu ,&nbsp;Yongtai Yang ,&nbsp;Weidong Zhu","doi":"10.1016/j.rcim.2024.102897","DOIUrl":"10.1016/j.rcim.2024.102897","url":null,"abstract":"<div><div>Aero-engine nacelle acoustic liners are complex curved surface subassemblies with tens of thousands of dense acoustic holes for noise reduction. Traditional robotic drilling systems with a single spindle and conventional teaching programming cannot meet the high-quality and high-efficiency drilling requirements for nacelle acoustic liners. This paper developed a novel robotic multi-spindle drilling system, which integrates standard industrial robots with a multi-spindle drilling end-effector to drill acoustic holes on an acoustic liner. The task planning strategy and offline programming method are investigated for the robotic multi-spindle drilling of the acoustic liner. A dedicated offline programming software capable of quickly generating robotic machining programs has been designed and developed. A precise acoustic hole arrangement applicable to curved drilling zones is demonstrated. The virtual surrogate hole is introduced to target the array layout of the developed end-effector's multiple spindles. A virtual surrogate hole generation method is proposed based on the minimum mutually exclusive set cover and the greedy algorithm. After that, a virtual surrogate hole layout optimization method is developed using an adaptive genetic annealing algorithm. Then, the frame chain is constructed as the kinematic foundation in robotic multi-spindle drilling of a nacelle acoustic liner. The drilling pose planning of the multi-spindle end-effector based on normal vectors and coordinates of acoustic hole points covered by virtual surrogate holes is explored. And a multi-spindle drilling path planning algorithm is developed using the genetic algorithm. To drill the aero-engine nacelle of a large aircraft, an offline programming software for robotic multi-spindle drilling of the nacelle acoustic liner is developed by integrating the methods above. A case study of multi-spindle drilling task planning of a nacelle acoustic liner is carried out. The case study results indicate that, compared to traditional single-spindle robotic drilling systems, the developed multi-spindle drilling system increases drilling efficiency by approximately 347 %. Using the proposed multi-spindle drilling path optimization algorithm, the drilling path has been shortened by 84.8 %. These results validate the effectiveness of the proposed series of drilling task planning methods and the developed offline programming software, which significantly enhance drilling efficiency while meeting the technical requirements for drilling acoustic holes on the acoustic liner.</div></div>","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"92 ","pages":"Article 102897"},"PeriodicalIF":9.1,"publicationDate":"2024-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142637643","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":"Human-in-the-loop Multi-objective Bayesian Optimization for Directed Energy Deposition with in-situ monitoring","authors":"João Sousa ,&nbsp;Armando Sousa ,&nbsp;Frank Brueckner ,&nbsp;Luís Paulo Reis ,&nbsp;Ana Reis","doi":"10.1016/j.rcim.2024.102892","DOIUrl":"10.1016/j.rcim.2024.102892","url":null,"abstract":"<div><div>Directed Energy Deposition (DED) is a free-form metal additive manufacturing process characterized as toolless, flexible, and energy-efficient compared to traditional processes. However, it is a complex system with a highly dynamic nature that presents challenges for modeling and optimization due to its multiphysics and multiscale characteristics. Additionally, multiple factors such as different machine setups and materials require extensive testing through single-track depositions, which can be time and resource-intensive. Single-track experiments are the foundation for establishing optimal initial parameters and comprehensively characterizing bead geometry, ensuring the accuracy and efficiency of computer-aided design and process quality validation. We digitized a DED setup using the Robot Operating System (ROS 2) and employed a thermal camera for real-time monitoring and evaluation to streamline the experimentation process. With the laser power and velocity as inputs, we optimized the dimensions and stability of the melt pool and evaluated different objective functions and approaches using a Response Surface Model (RSM). The three-objective approach achieved better rewards in all iterations and, when implemented in a real setup, allowed to reduce the number of experiments and shorten setup time. Our approach can minimize waste, increase the quality and reliability of DED, and enhance and simplify human-process interaction by leveraging the collaboration between human knowledge and model predictions.</div></div>","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"92 ","pages":"Article 102892"},"PeriodicalIF":9.1,"publicationDate":"2024-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142637685","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A two-stage dynamic model updating method for the FRF prediction of the robotized mobile machining equipment","authors":"Zijian Ma ,&nbsp;Fugui Xie ,&nbsp;Xin-Jun Liu","doi":"10.1016/j.rcim.2024.102895","DOIUrl":"10.1016/j.rcim.2024.102895","url":null,"abstract":"<div><div>In the coming decades, robotized mobile machining equipment (RMME) is possible to evolve as a new branch of machine tools due to its exceptional flexibility. The frequency response function (FRF) serves as a theoretical foundation in controlling the vibration deformations that significantly limit the material removal efficiency of RMME. Model updating, aimed at minimizing errors between the theoretical model and the physical prototype, is essential to predict the FRF accurately. However, updating the dynamic model of RMME, characterized by non-mechanical boundary conditions, complex lightweight components, and low-stiffness structures, presents difficulties in computational efficiency and updating posture-dependent parameters. To solve these issues, the prediction error generation mechanism is first analyzed to confirm the error types that need to be eliminated in model updating. A two-stage model updating method that can separately update the robot structure and boundary-related parameters is proposed to rapidly update the dynamic model under various machining tasks. The interface reduction technique that can decrease the model order is introduced to reduce the computational consumption, and an approach to fast update such interface reduction substructures is put forward to avoid the reiterative model reduction during updating. An updating method for posture-dependent parameters based on multi-objective optimization is designed to control the multiple solution issues by generating many feasible solutions, ensuring the prediction effects for non-updated postures. The experimental results indicate that updating structural parameters in stage I and adsorption surface parameters in stage II results in mean error reduction percentages of 58.79 % and 48.30 %, respectively. Additionally, the natural frequencies and the mode shapes can also be predicted by the updated model. Comparative analysis with various controlled groups confirms the advantages of utilizing posture-dependent parameters in prediction accuracy and adopting the two-stage model updating method in efficiency. The proposed method can also be applied to other RMMEs.</div></div>","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"92 ","pages":"Article 102895"},"PeriodicalIF":9.1,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142593790","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":"Variable impedance control on contact-rich manipulation of a collaborative industrial mobile manipulator: An imitation learning approach","authors":"Zhengxue Zhou,&nbsp;Xingyu Yang,&nbsp;Xuping Zhang","doi":"10.1016/j.rcim.2024.102896","DOIUrl":"10.1016/j.rcim.2024.102896","url":null,"abstract":"<div><div>Variable impedance control (VIC) endows robots with the ability to adjust their compliance, enhancing safety and adaptability in contact-rich tasks. However, determining suitable variable impedance parameters for specific tasks remains challenging. To address this challenge, this paper proposes an imitation learning-based VIC policy that employs observations integrated with RGBD and force/torque (F/T) data enabling a collaborative mobile manipulator to execute contact-rich tasks by learning from human demonstrations. The VIC policy is learned through training the robot in a customized simulation environment, utilizing an inverse reinforcement learning (IRL) algorithm. High-dimensional demonstration data is encoded by integrating a 16-layer convolutional neural network (CNN) into the IRL environment. To minimize the sim-to-real gap, contact dynamic parameters in the training environment are calibrated. Then, the learning-based VIC policy is comprehensively trained in the customized environment and its transferability is validated through an industrial production case involving a high precision peg-in-hole task using a collaborative mobile manipulator. The training and testing results indicate that the proposed imitation learning-based VIC policy ensures robust performance for contact-rich tasks.</div></div>","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"92 ","pages":"Article 102896"},"PeriodicalIF":9.1,"publicationDate":"2024-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142585486","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimal model-based path planning for the robotic manipulation of deformable linear objects","authors":"Andrea Monguzzi,&nbsp;Tommaso Dotti,&nbsp;Lorenzo Fattorelli,&nbsp;Andrea Maria Zanchettin,&nbsp;Paolo Rocco","doi":"10.1016/j.rcim.2024.102891","DOIUrl":"10.1016/j.rcim.2024.102891","url":null,"abstract":"<div><div>The robotic manipulation of deformable linear objects (DLOs), such as cables, is a valuable yet complex skill. In particular, to realize tasks like cable routing and wire harness assembly, it is required that two robotic arms, grasping the ends of a DLO, move it from an initial shape to a final one where cable assembly can be performed. The manipulation must be performed following a collision-free path and avoiding stretching and excessively deforming it. We address this problem by proposing an optimal model-based path planning strategy. Specifically, a hierarchical optimization strategy is defined to perform path planning, exploiting a mass–spring DLO dynamic model that we enhance to handle a generic equilibrium condition for the DLO. Furthermore, we model the interaction of the DLO with objects like clips used in assembly operations. We also deal with the estimation of the DLO stiffness to properly tune the model parameters. The effectiveness of our methodology is assessed via experimental tests, where a dual-arm robot executes the planned paths manipulating several DLOs with different mechanical properties. Finally, the method is exploited to execute a wire harness assembly task.</div></div>","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"92 ","pages":"Article 102891"},"PeriodicalIF":9.1,"publicationDate":"2024-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142577804","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":"Design synthesis, modeling, control strategies, and fabrication methods of compliant grippers for micromanipulation and micromanipulator: A comprehensive review","authors":"Hieu Giang Le ,&nbsp;Nhat Linh Ho ,&nbsp;Thanh-Phong Dao","doi":"10.1016/j.rcim.2024.102893","DOIUrl":"10.1016/j.rcim.2024.102893","url":null,"abstract":"<div><div>In robotic and automation industry, micromanipulation and micromanipulator have recognized significant advancements due to they are involved in handling of micro-sized parts from a few to hundreds of micrometers. In order to perform such precise grasping tasks, compliant grippers have been increasingly developed, and they have critically significant contributions in the high precision micromanipulation and micromanipulator. This article aims to present a comprehensive review on the state-of-the-art development of compliant grippers. This review focuses on design synthesis, modeling methods, control strategies, and fabrication technologies for compliant grippers. Each section is deeply analyzed and discussed. This paper identifies ongoing challenges and outlines future prospects for developing compliant grippers. The achieved results of this review can provide and inspire helpful insights in ultra-high precision micromanipulation and micromanipulator.</div></div>","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"92 ","pages":"Article 102893"},"PeriodicalIF":9.1,"publicationDate":"2024-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142571632","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":"Self-training-based approach with improved XGBoost for aluminum alloy casting quality prediction","authors":"Haonan Wang ,&nbsp;Quanzhi Sun ,&nbsp;Jun Wu ,&nbsp;Xuxia Zhang ,&nbsp;Weipeng Liu ,&nbsp;Tao Peng ,&nbsp;Renzhong Tang","doi":"10.1016/j.rcim.2024.102890","DOIUrl":"10.1016/j.rcim.2024.102890","url":null,"abstract":"<div><div>The revolutionary advances in integrated components in current automotive industry have led to a sharply rising demand for aluminum alloy castings. Targeted quality inspection is thus proposed for components manufacturers to achieve high responsiveness and low operational cost. This suggests casting machine manufacturers to integrate advanced quality prediction functions into the next generation of intelligent casting machines. However, acquiring ample quality inspection data is essential for implementing such functions, which is often challenging, if not infeasible, due to practical issues such as data proprietorship or privacy. Self-training is a good candidate for dealing with scarce labeled data, and XGBoost is commonly used as the base classifier. However, misclassification of unlabeled data happens using XGBoost, which could lead to incorrect pseudo-label assignments, eventually resulting in higher misclassification rate. To address this challenge, a self-training and improved XGBoost-based aluminum alloy casting quality prediction approach is proposed. This approach integrates the classification loss of unlabeled data in the objective function as a new regularization term and considers first and second partial derivatives of the classification loss function for unlabeled data in the leaf node's weight score. The proposed approach penalizes those classification models that misclassify unlabeled data, thereby improves quality prediction performance. To evaluate the effectiveness of our approach, a casting machine manufacturer was collaborated to conduct a case study. The results on three-type casting quality prediction demonstrate that our approach could achieve an accuracy, precision, recall and F1 score of 93.2 %, 90 %, 64.2 %, and 0.75, respectively, outperforming all compared approaches. The approach supports casting machine manufacturers to pre-train a casting quality prediction models with scarce labeled data, enabling swift deployment and customization for targeted quality inspection.</div></div>","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"92 ","pages":"Article 102890"},"PeriodicalIF":9.1,"publicationDate":"2024-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142571631","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}