Robotics and Computer-integrated Manufacturing最新文献

{"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}

{"title":"Adaptively sampled distance functions: A unifying digital twin representation for advanced manufacturing","authors":"Sam Pratt ,&nbsp;Tadeusz Kosmal ,&nbsp;Christopher Williams","doi":"10.1016/j.rcim.2024.102877","DOIUrl":"10.1016/j.rcim.2024.102877","url":null,"abstract":"<div><div>Digital twin tools for additive manufacturing (AM) are constrained by the underlying representations of component geometry that are currently in wide use. Mesh, voxel, and parametric surface representations require numerous conversions to intermediate representations at multiple points throughout the processing chain. Each conversion introduces additional error in the geometric representation and complicates comparison of <em>in-situ</em> process sensor data to the as-designed component. Additionally, the limited interoperability of the various representations produced throughout the process chain limit the insights available from current digital twin tools. We introduce a novel framework based on a unifying geometric representation that serves the complete AM digital thread. The presented GPU-accelerated, adaptively sampled distance function (ASDF) framework serves as a foundation for component design and path planning tools, especially for real-time path planning in AM, as well as provides a baseline representation of geometry from control systems, and enables rapid comparison of <em>in-situ</em> sensor data to the as-designed model without intermediate conversion, greatly reducing the burden of reducing such data to usable process insights.</div></div>","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"92 ","pages":"Article 102877"},"PeriodicalIF":9.1,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142534212","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":"Trajectory error compensation method for grinding robots based on kinematic calibration and joint variable prediction","authors":"Kaiwei Ma ,&nbsp;Fengyu Xu ,&nbsp;Qingyu Xu ,&nbsp;Shuang Gao ,&nbsp;Guo-Ping Jiang","doi":"10.1016/j.rcim.2024.102889","DOIUrl":"10.1016/j.rcim.2024.102889","url":null,"abstract":"<div><div>Trajectory accuracy, a crucial metric in assessing the dynamic performance of grinding robots, is influenced by the uncertain movement of the tool center point, directly impacting the surface quality of processed workpieces. This article introduces an innovative method for compensating trajectory errors. Initially, a strategy for error compensation is derived using differential kinematics theory. Subsequently, a robot kinematic calibration method utilizing ring particle swarm optimization (RPSO) is proposed to address static errors in the grinding robot. Simultaneously, a method for predicting robot joint variables based on a dual-channel feedforward neural network (DCFNN) is designed to mitigate dynamic errors. Finally, a simulation platform is developed to validate the proposed method. Simulation analysis using extensive data demonstrates an 89.3% improvement in absolute position accuracy and a 74.2% reduction in error fluctuation range, outperforming sparrow search algorithm (SSA), improved mayfly algorithm (IMA), multi-representation integrated predictive neural network (MRIPNN), etc. Algorithmic comparison reveals that kinematic calibration significantly reduces the average trajectory error, while joint variable prediction notably minimizes error fluctuation. Validation through trajectory straightness testing and a 3D printing propeller grinding experiment achieves a trajectory straightness of 0.2425 mm. Implementing this method enables achieving 86.1% surface machining allowance within tolerance, making it an optimal solution for grinding robots.</div></div>","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"92 ","pages":"Article 102889"},"PeriodicalIF":9.1,"publicationDate":"2024-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142534211","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 hybrid model in a nonlinear disturbance observer for improving compliance error compensation of robotic machining","authors":"Ali Khishtan ,&nbsp;Seong Hyeon Kim ,&nbsp;Jihyun Lee","doi":"10.1016/j.rcim.2024.102887","DOIUrl":"10.1016/j.rcim.2024.102887","url":null,"abstract":"<div><div>The joint deflection of robots in machining degrades product accuracy. Compliance error compensation has been investigated to reduce the static deflection of robotic machining. The challenge in compliance error compensation is accurately measuring the deflection or cutting force. External sensors have been used to measure them in robotic machining, but it is not practical. The authors proposed a nonlinear disturbance observer to indirectly measure the cutting force online in robotic machining in the previous study. The observer, however, needs to utilize the robot model that includes characteristics of high nonlinearity, uncertainty, and high dynamic variation for different robot postures. After investigating these challenges of modeling, this paper proposes a hybrid modeling approach combining a physics-based model with a new empirical friction model, and a data-driven model to accurately estimate the cutting force while minimizing the error of the robot's mathematical model. The joint torque calculated from the hybrid model can cover the effect of joints' postures and speeds on the varying dynamic in its workspace. Real-time optimization just before cutting is also proposed to adapt to the real-time joint's motion conditions. The experimental results from aluminum multi-axis cutting show that the estimated cutting force via the nonlinear disturbance observer based on the proposed hybrid modeling approach can improve its accuracy up to 45% and 74% in the <em>x</em> and <em>y</em> directions respectively, compared to the physics-based modeling approach. The deflection of the tool center point can be compensated by using a compliance error compensation method up to 79.1% and 75.4% in the <em>x</em> and <em>y</em> directions, respectively, at 0.5 <em>mm/s</em> feed rate, and up to 77.2% and 78.9% at 3 <em>mm/s</em> feed rate. Consequently, the approaches developed in this paper can solve the problems of conventional robot modeling and improve the accuracy of robot machining.</div></div>","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"92 ","pages":"Article 102887"},"PeriodicalIF":9.1,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142534213","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":"Tool breakage monitoring driven by the real-time predicted spindle cutting torque using spindle servo signals","authors":"Yinghao Cheng ,&nbsp;Yingguang Li ,&nbsp;Guangxu Li ,&nbsp;Xu Liu ,&nbsp;Jinyu Xia ,&nbsp;Changqing Liu ,&nbsp;Xiaozhong Hao","doi":"10.1016/j.rcim.2024.102888","DOIUrl":"10.1016/j.rcim.2024.102888","url":null,"abstract":"<div><div>Monitoring tool breakage during computer numerical control machining is essential to ensure machining quality and equipment safety. In consideration of the low cost in long-term use and the non-invasiveness to workspace, using servo signals of machine tools to monitor tool breakage has been viewed as the solution that has great potential to be applied in real industry. However, because machine tool servo signals can only partially and indirectly reflect tool conditions, the accuracy and reliability of existing methods still need to be improved. To overcome this challenge, a novel two-step data-driven tool breakage monitoring method using spindle servo signals is proposed. Since spindle cutting torque is acknowledged as one of the most effective and reliable physical signals for detecting tool breakage, it is introduced as the key intermediate variable from spindle servo signals to tool conditions. The monitored spindle servo signals are used to predict the spindle cutting torque in real time based on a long short-term memory neural network, and then the predicted spindle cutting torque is used to detect tool breakage based on a one-dimensional convolutional neural network. The experimental results show that the proposed method can accurately predict the spindle cutting torque for normal tools and broken tools. Compared with the tool breakage monitoring methods that directly use spindle servo signals, the proposed method has higher detection accuracy and more reliable detection results, and the performance is more stable when increasing the detection frequency and decreasing training data.</div></div>","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"92 ","pages":"Article 102888"},"PeriodicalIF":9.1,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142433852","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":"Communicating robots’ intent through visual cues enhances human anticipatory behavior in human–dual robot collaboration","authors":"Loizos Psarakis,&nbsp;Dimitris Nathanael,&nbsp;Nicolas Marmaras","doi":"10.1016/j.rcim.2024.102886","DOIUrl":"10.1016/j.rcim.2024.102886","url":null,"abstract":"<div><div>The present study aims at exploring the effect of communicating robots’ intent through visual cues, to the human on a complex human-robot collaborative task. Specifically, it aims to investigate (i) whether the use of such “anticipatory cues” will have a positive effect on task efficiency, human safety and collaborating fluency, (ii) the degree of this effect with varying robots’ speed and (iii) whether a retention effect will be observed after the removal of the cues. For exploring these issues, a human - dual robot industrial assembly task was designed in a Virtual Reality simulation environment and testing was carried out by 64 volunteer participants. Results showed that communicating robots’ intent through visual cues enhanced human anticipatory behavior, resulting in a significant improvement in human safety, team efficiency and collaborative fluency, in conjunction with a favorable subjective tendency towards the robots. However, the positive effect of the anticipatory cues was not found to increase with higher robot speed. Finally, the findings suggest that prior exposure to the cues made participants more confident in coordinating with the robots, even when the cues were removed from them, thus retaining their prior efficiency but with a negative effect on safety. In summary, the study provides evidence that use of anticipatory visual cues accelerates the legibility of robot movement and fosters human confidence and familiarization. The use of anticipatory cues seems promising for high-pace, non-repetitive interactions with collaborative robots or as a training aid in more repetitive human-robot collaborative tasks.</div></div>","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"92 ","pages":"Article 102886"},"PeriodicalIF":9.1,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142422723","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 point cloud registration algorithm considering multi-allowance constraints for robotic milling of complex parts","authors":"Jixiang Yang,&nbsp;Jinxian Zhang,&nbsp;Tianshu Song,&nbsp;Han Ding","doi":"10.1016/j.rcim.2024.102885","DOIUrl":"10.1016/j.rcim.2024.102885","url":null,"abstract":"<div><div>Adaptive allocation of the machining allowance is the crucial factor in ensuring the machining accuracy of complex parts. In this work, we present a multi-objective constraint registration method. First, an improved point cloud segmentation method is developed by combining point search and region data expansion algorithms. Afterward, the machining allowance is accurately calculated by using statistical analysis and multi-point sampling strategies to enhance the calculation accuracy of the point-to-triangular patch distance. Finally, a registration objective function is established by considering the allowance constraints of various geometric regions of the workpiece, and the particle swarm optimization algorithm is used to solve the optimum solution. The proposed multi-constraint registration method realizes optimal allocation of the allowance in different regions, which offers a reference coordinate system for the robotic milling of complex free-formed parts. Simulation and experimental results reveal that the developed method satisfies the minimum registration error while ensuring the allocation of allowance in the robotic milling of the casing cavity compared with other methods.</div></div>","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"92 ","pages":"Article 102885"},"PeriodicalIF":9.1,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142359647","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":"Sigmoid angle-arc curves: Enhancing robot time-optimal path parameterization for high-order smooth motion","authors":"Shize Zhao,&nbsp;Tianjiao Zheng,&nbsp;Chengzhi Wang,&nbsp;Ziyuan Yang,&nbsp;Tian Xu,&nbsp;Yanhe Zhu,&nbsp;Jie Zhao","doi":"10.1016/j.rcim.2024.102884","DOIUrl":"10.1016/j.rcim.2024.102884","url":null,"abstract":"<div><div>Trajectory planning is crucial in the motion planning of robots, where finding the time-optimal path parameterization (TOPP) of a given path subject to kinodynamic constraints is an important component of trajectory planning. The tangential discontinuity at the intersection of continuous line segments limits the speed of trajectory planning and can easily cause jitter and over-constraint phenomena. Smooth transitions at corners can be achieved by inserting parameter spline curves. However, due to the insensitivity of parameter spline curves to arc length, their performance in the application of the TOPP algorithm, which relies on the higher-order robot kinematics smoothness (i.e., the function <span><math><mrow><mi>q</mi><mrow><mo>(</mo><mi>s</mi><mo>)</mo></mrow></mrow></math></span> of the configuration space to the Cartesian space), fails to meet expectations.</div><div>A smoothing method suitable for the TOPP algorithm is proposed: Sigmoid Angle-Arc Curve (SAAC). This curve exhibits excellent performance in smooth corner transitions of the TOPP algorithm and is parameterized using arc length. The curvature and geometry of its curves can be expressed analytically in terms of arc lengths. Compared with the traditional B-spline method and the symmetric Euler spiral blending (SE-spiral), SAAC can provide smoother <span><math><msup><mrow><mi>C</mi></mrow><mrow><mn>2</mn></mrow></msup></math></span> robot kinematics characteristics. Using the TOPP algorithm based on SAAC can significantly enhance the robustness of the TOPP algorithm, significantly reduce jerks, and reduce the time required for movement.</div></div>","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"92 ","pages":"Article 102884"},"PeriodicalIF":9.1,"publicationDate":"2024-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142326346","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 survey on potentials, pathways and challenges of large language models in new-generation intelligent manufacturing","authors":"Chao Zhang ,&nbsp;Qingfeng Xu ,&nbsp;Yongrui Yu ,&nbsp;Guanghui Zhou ,&nbsp;Keyan Zeng ,&nbsp;Fengtian Chang ,&nbsp;Kai Ding","doi":"10.1016/j.rcim.2024.102883","DOIUrl":"10.1016/j.rcim.2024.102883","url":null,"abstract":"<div><div>Nowadays, Industry 5.0 starts to gain attention, which advocates that intelligent manufacturing should adequately consider the roles and needs of humans. In this context, how to enhance human capabilities or even liberate humans from the processes of perception, learning, decision-making, and execution has been one of the key issues to be addressed in intelligent manufacturing. Large language models (LLMs), as the breakthrough in new-generation artificial intelligence, could provide human-like interaction, reasoning, and replies suitable for various application scenarios, thus demonstrating significant potential to address the above issues by providing aid or becoming partners for humans in perception, learning, decision-making, and execution in intelligent manufacturing. The combination of LLMs and intelligent manufacturing has inherent advantages and is expected to become the next research hotspot. Hence, this paper primarily conducts a systematic literature review on the application of LLMs in intelligent manufacturing to identify the promising research topics with high potential for further investigations. Firstly, this paper reveals the concept, connotation, and foundational architecture of LLMs. Then, several typical and trending interdisciplinary LLM applications, such as healthcare, drug discovery, social &amp; economic, education, and software development, are summarized, on which an LLM-enabled intelligent manufacturing architecture is designed to provide a reference for applying LLMs in intelligent manufacturing. Thirdly, the specific pathways for applying LLMs in intelligent manufacturing are explored from the perspectives of design, production, and service. Finally, this paper identifies the limitations, barriers, and challenges that will be encountered during the research and application of LLMs in intelligent manufacturing, while providing potential research directions to address these limitations, barriers, and challenges.</div></div>","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"92 ","pages":"Article 102883"},"PeriodicalIF":9.1,"publicationDate":"2024-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142322543","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}