Youngsu Cho , Minsu Cho , Jongwoo Park, Byung-Kil Han, Young Hun Lee, Sung-Hyuk Song, Chanhun Park, Dong Il Park
{"title":"Strategic algorithm for cable wiring using dual arm with compliance control","authors":"Youngsu Cho , Minsu Cho , Jongwoo Park, Byung-Kil Han, Young Hun Lee, Sung-Hyuk Song, Chanhun Park, Dong Il Park","doi":"10.1016/j.rcim.2024.102924","DOIUrl":"10.1016/j.rcim.2024.102924","url":null,"abstract":"<div><div>A variety of electronic products are in daily use to serve a variety of needs. Electronic products require different types of cable harnesses for production. Nowadays, user preferences vary and change quickly. Therefore, a variety of small-volume products are made, and producing various kinds of complex harnesses to satisfy people’s needs is difficult. In robotic automation, the wiring harness assembly process in the manufacturing of deformable objects is challenging. Because of the characteristics of a deformable object, the manufacturing task cannot be standardized. However, relying solely on image sensors is not advisable, due to the challenges involved in recognizing complex cables with image sensors. Additionally, even when cable recognition is possible, it requires too much time. To address these issues, this paper introduces a strategic algorithm for the wiring harness assembly process. The algorithm minimizes the dependence on image sensors by enabling the use of a robotic dual-arm system. The proposed method includes techniques such as cable estimation, frictional models, and trajectory planning in the algorithms. On the basis of these methods, for a provided assembly board, the algorithm outputs a systematic process for wiring harness assembly. Experimental results validate the algorithm, demonstrating its good performance.</div></div>","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"93 ","pages":"Article 102924"},"PeriodicalIF":9.1,"publicationDate":"2024-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142888212","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":"Robotic grinding of curved parts with two degrees of freedom active compliant force-controlled end-effector using decoupling control algorithm","authors":"Haiqing Chen, Jixiang Yang, Han Ding","doi":"10.1016/j.rcim.2024.102935","DOIUrl":"10.1016/j.rcim.2024.102935","url":null,"abstract":"<div><div>This paper proposes a novel two degrees of freedom (2-DOF) active compliant force-controlled end-effector (EE) using decoupling control algorithm to improve grinding efficiency, material removal accuracy, and surface quality of the curved parts for robotic grinding. First, a robotic grinding system is described, which consists of an industrial robot for tool-path control and a novel 2-DOF compliant EE to improve grinding efficiency and compliance. Second, the dynamic relationship between the friction coefficient and the normal force is established to develop an online prediction model for the normal force. The tangential tool tip displacement model is also established. A force-position decoupling control algorithm, which comprises force–position decoupling and fuzzy force–position switching controllers, is then proposed to improve the normal force and the tangential tool tip displacement control accuracy of the 2-DOF compliant EE. Finally, the developed methodology is validated through grinding experiments to confirm its effectiveness. The grinding results show that under the premise of ensuring the neglectable tangential tool tip displacement error to the original grinding process, the developed 2-DOF compliant EE with decoupling control demonstrates similar high force control accuracy and grinding depth accuracy to the 1-DOF compliant EE, and the machining efficiency is improved by approximately 30 % compared to that of the 1-DOF compliant EE. Compared with the traditional 2-DOF rigid EE using hybrid control, the normal force and tangential tool tip displacement control errors of the developed 2-DOF compliant EE with decoupling control are reduced by approximately 60 % and 33 %, respectively, and the overshoot is reduced from 30 % to almost 0. The developed 2-DOF compliant EE with decoupling control improves the grinding depth accuracy and surface quality compared to the traditional 2-DOF rigid EE with hybrid control.</div></div>","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"93 ","pages":"Article 102935"},"PeriodicalIF":9.1,"publicationDate":"2024-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142888209","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}
Jun Hwan Park , Seungeun Lim , Changmo Yeo , Youn-Kyoung Joung , Duhwan Mun
{"title":"DFGAT for recognizing design features from a B-rep model for mechanical parts","authors":"Jun Hwan Park , Seungeun Lim , Changmo Yeo , Youn-Kyoung Joung , Duhwan Mun","doi":"10.1016/j.rcim.2024.102938","DOIUrl":"10.1016/j.rcim.2024.102938","url":null,"abstract":"<div><div>Design feature recognition plays a crucial role in digital manufacturing and is a key technology in automatic design verification. Traditional methods and deep learning approaches provide various strategies for feature recognition. However, these methods primarily address part classification or machining feature recognition, with limited research focusing on design feature recognition. To address this gap, a novel deep learning network called the design feature graph attention network (DFGAT) was proposed specifically for design feature recognition. In this study, the original boundary representation (B-rep) model is first converted into graph representation. Design feature recognition is then achieved using the DFGAT, which is based on the GAT. Additionally, the dataset generation process was generalized to efficiently train the deep learning model. To validate the performance of the DFGAT, experiments were conducted to recognize the representative faces of design features, such as snap-fit hooks, cups, and plates, in the EIF_Panel, Real_Panel, and Anemometer models. The experiments demonstrated F1-scores of 0.9924, 0.9982, and 1.0000.</div></div>","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"93 ","pages":"Article 102938"},"PeriodicalIF":9.1,"publicationDate":"2024-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142867623","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}
Shizhong Tan , Congcong Ye , Chengxing Wu , Jixiang Yang , Han Ding
{"title":"A contour error prediction method for tool path correction using a multi-feature hybrid model in robotic milling systems","authors":"Shizhong Tan , Congcong Ye , Chengxing Wu , Jixiang Yang , Han Ding","doi":"10.1016/j.rcim.2024.102936","DOIUrl":"10.1016/j.rcim.2024.102936","url":null,"abstract":"<div><div>Achieving high precision in robotic milling presents significant challenges due to inherent errors caused by various factors such as robot stiffness deformation and uneven machining allowances in large workpieces. Traditional error corrected methods often fall short in effectively addressing the complexity and dynamic nature of such errors. To address these challenges, a contour error prediction model has been proposed by using a combination of Gaussian Processes and a CNN-BiLSTM architecture. Firstly, extract the potential error features, including the robot's posture and stiffness information, as well as the workpiece's machining allowance during the milling process. Then, process these features to create a uniformly structured training set. Subsequently, develop a CNN-BiLSTM neural network model to realize an accurate contour error prediction, where the CNN layers are responsible for extracting hidden local features from the structured data, while the BiLSTM layers capture temporal correlations and hidden features related to tool path. Finally, validate on a saddle-shaped workpiece with surface features similar to those found in aero-engine casing cavities. The results demonstrate that the fusion-based error prediction model effectively reduces the maximum contour error from 0.9629 mm to 0.4881 mm, and decreases the mean absolute contour error from 0.7171 mm to 0.3048mm, representing reductions of 49.30 % and 57.40 %, respectively. These reductions well validate the effectiveness of the proposed method.</div></div>","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"93 ","pages":"Article 102936"},"PeriodicalIF":9.1,"publicationDate":"2024-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142867624","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}
Pierre-Luc Beaulieu, Thierry Laliberté, Simon Foucault, Clément Gosselin
{"title":"Synthesis and prototyping of a backdrivable parallel robot for metal finishing tasks","authors":"Pierre-Luc Beaulieu, Thierry Laliberté, Simon Foucault, Clément Gosselin","doi":"10.1016/j.rcim.2024.102934","DOIUrl":"10.1016/j.rcim.2024.102934","url":null,"abstract":"<div><div>This article presents the synthesis, control and experimental validation of a backdrivable three-degree-of-freedom translational mini robot used to control the interaction between a robot and a machined part during finishing tasks, such as polishing, sanding and deburring without requiring the use of a force/torque sensor. The mini robot acts as an active contact flange, allowing an industrial robot (the macro robot) to adapt to a part using an impedance control algorithm. Firstly, different three-degree-of-freedom parallel robot architectures are compared and the most suitable architecture is selected. Geometrical properties are chosen for the robot and the physical capabilities of the architecture are predicted to ensure that the design criteria are satisfied. An impedance control algorithm is then developed for the mini robot. The macro-mini system is formed by installing the mini robot on a gantry robot. Sanding tests are carried out in order to validate the performance of the system and the mini robot is compared to other contact flanges already available on the market. Finally, a method allowing the determination of the magnitude of the friction forces in the mini robot is presented and a preliminary friction compensation algorithm is developed. As opposed to existing tools, the novel mini robot proposed in this work is based on a compact parallel architecture, which makes it possible to ensure the backdrivability of the system in three directions. An impedance control algorithm can therefore be implemented thereby providing stability even with stiff environments and eliminating the need for a force/torque sensor.</div></div>","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"93 ","pages":"Article 102934"},"PeriodicalIF":9.1,"publicationDate":"2024-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143150860","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}
Domenico Spensieri, Edvin Å blad, Raad Salman, Johan S. Carlson
{"title":"A unified sampling method for optimal feature coverage and robot placement","authors":"Domenico Spensieri, Edvin Å blad, Raad Salman, Johan S. Carlson","doi":"10.1016/j.rcim.2024.102932","DOIUrl":"10.1016/j.rcim.2024.102932","url":null,"abstract":"<div><div>Designing a robot line includes the critical decision about the number of robots needed to carry out all the tasks in the stations and their placement. Similarly, having a robot manipulator mounted on a mobile base, such as an Automated Guided Vehicle (AGV), needs a careful choice of the base positions to minimize cycle time for the operations. In this paper, we solve both the robot placement and the AGV positioning problems by relating them to feature coverage applications, where the challenge is to place cameras (or other sensors) to inspect all points on a workpiece for metrology tasks. These similarities allow us to design an efficient divide&conquer-based algorithm which can be adapted to solve all three problems above, where finding the minimum number of positions for sensors, AGVs and robots is crucial to reduce cycle time and costs.</div><div>The algorithm is divided in two parts: the first one is responsible for identifying candidate positions, whereas the second solves a set covering problem. We show that these two parts can even be interlaced to obtain high-quality solutions in short time.</div><div>A successful computational study has been carried out with both artificial instances and three industrial scenarios, ranging from laser sensor inspection cells in the aerospace industry, to an automated cleaning room, and ending with a stud welding station for automotive applications.</div><div>The results show that geometric and industrial tests, even accounting for kinematics and distance queries, can be handled with high accuracy in reasonable computing time.</div></div>","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"93 ","pages":"Article 102932"},"PeriodicalIF":9.1,"publicationDate":"2024-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142867626","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}
Guolong Zhang , Guilin Yang , Yimin Deng , Chin-yin Chen , Zaojun Fang , Junjie Li
{"title":"Jerk-optimal force and motion synchronous planning for a 3-DOF translational force-controlled end-effector","authors":"Guolong Zhang , Guilin Yang , Yimin Deng , Chin-yin Chen , Zaojun Fang , Junjie Li","doi":"10.1016/j.rcim.2024.102931","DOIUrl":"10.1016/j.rcim.2024.102931","url":null,"abstract":"<div><div>The 3-DOF Translational Force-controlled End-effector (TFE) based on 3-P(UU)<sub>2</sub> Parallel Mechanism (PM) and pneumoelectric actuator is developed for polishing process performed by industrial robots, in which synchronous force and motion planning is critical to enhance the polishing performance. However, conventional planning methods are mainly developed to generate the trajectory for robotic motion control. Utilizing periodic splines, a new jerk-optimal Force and Motion Synchronous Planning (FMSP) method is proposed for the 3-DOF TFE to improve the force control stability between the tool and environment. Both the kinematics of the 3-DOF translational PM and the dynamics of the hybrid serial-parallel and macro-mini robotic system are established through screw theory. By introducing septuple B-splines for motion trajectory and cubic splines for contact force with periodic boundary conditions, the jerk-optimal performance index of motion and force is employed to formulate the FMSP model in Cartesian space. Simulation and experimental results demonstrate that the high-order continuity of the active driving force, moving acceleration and jerk-optimal performance index generated by FMSP is preferable compared to the Trajectory Planning with Point-to-point Force (TPWPF) and the Force-motion Linear Interpolation (FMLI) methods. The unloaded force peaks caused by the motion impact are reduced by 21 % and 22.6 % along <em>x</em> and <em>y</em> direction, respectively. Furthermore, the peaks of the contact force between the tool and workpiece decrease by 31.5 % and 20.4 % owing to slighter systemic vibration and impact. The FMSP method for force-controlled end-effector shows great potential in robotic continuous contact operations.</div></div>","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"93 ","pages":"Article 102931"},"PeriodicalIF":9.1,"publicationDate":"2024-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142867635","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}
Yiwen Hu , Hongliang Dong , Jianhua Liu , Cunbo Zhuang , Feng Zhang
{"title":"A learning-guided hybrid genetic algorithm and multi-neighborhood search for the integrated process planning and scheduling problem with reconfigurable manufacturing cells","authors":"Yiwen Hu , Hongliang Dong , Jianhua Liu , Cunbo Zhuang , Feng Zhang","doi":"10.1016/j.rcim.2024.102919","DOIUrl":"10.1016/j.rcim.2024.102919","url":null,"abstract":"<div><div>Integrated process planning and scheduling (IPPS) is a crucial component of an intelligent manufacturing system. While most existing studies have focused on the manufacturing workshop, less attention has been given to the assembly and test workshops, which typically include reconfigurable manufacturing cells (RMCs). Therefore, this paper focuses on IPPS with reconfigurable manufacturing cells (IPPS_RMCs) in the context of assembly and test workshops. The objective of IPPS_RMCs is to minimize the makespan and total weighted tardiness, taking into account priority constraints and capability conversion limits of RMCs. To address and optimize this problem, a learning-guided hybrid genetic algorithm (LG_HGA) is proposed, which utilizes chromosome encoding to solve the process planning and scheduling problem synchronously. The LG_HGA incorporates NSGA-II as the global search and employs a learning-guided multi-neighborhood search (LG_MNS) to achieve a better balance between exploration and exploitation. In the global search phase, a problem-based methodology for gene operation is introduced. The LG_MNS consists of four neighborhood structures, based on critical paths and heuristic rules. Additionally, the learning-guided mechanism involves using a decision tree regression model to learn data from the knowledge base and determine how to perform local search. Through case tests of various sizes, the experimental results demonstrate that LG_HGA outperforms several advanced multi-objective evolutionary algorithms due to the proposed improved genetic operations, neighborhood structure, and learning mechanism.</div></div>","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"93 ","pages":"Article 102919"},"PeriodicalIF":9.1,"publicationDate":"2024-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143150955","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}
Sean Rescsanski , Rainer Hebert , Azadeh Haghighi , Jiong Tang , Farhad Imani
{"title":"Towards intelligent cooperative robotics in additive manufacturing: Past, present, and future","authors":"Sean Rescsanski , Rainer Hebert , Azadeh Haghighi , Jiong Tang , Farhad Imani","doi":"10.1016/j.rcim.2024.102925","DOIUrl":"10.1016/j.rcim.2024.102925","url":null,"abstract":"<div><div>Additive manufacturing (AM) technologies have undergone significant advancements through the integration of cooperative robotics additive manufacturing (C-RAAM) platforms. By deploying AM processes on the end effectors of multiple robotic arms, not only are traditional constraints such as limited build volumes circumvented, but systems also achieve accelerated fabrication speeds, cooperative sensing capabilities, and in-situ multi-material deposition. Despite advancements, challenges remain, particularly regarding defect generation including voids, cracks, and residual stress. Various factors contribute to these issues, including toolpath planning (i.e., slicing strategies), part decomposition for cooperative printing, and motion planning (i.e., path and trajectory planning). This review first examines the critical aspects of system control for C-RAAM systems consisting of slicing and motion planning. The methods for the mitigation of defects through the adjustment of these aspects and the process parameters of AM methods are then described in the context of how they modify the AM process: pre-process, inter-layer (i.e., during layer pauses), and mid-layer (i.e., during material deposition). The application of advanced sensing technologies, including high-resolution cameras, laser scanners, and thermal imaging, for capturing of micro, meso, and macro-scale defects is explored. The role of digital twins is analyzed, emphasizing their capability to simulate and predict manufacturing outcomes, enabling preemptive adjustments to prevent defects. Finally, the outlook and future opportunities for developing next-generation C-RAAM systems are outlined.</div></div>","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"93 ","pages":"Article 102925"},"PeriodicalIF":9.1,"publicationDate":"2024-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142816574","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}
Nieqing Cao , Jaewoo Kim , Abdelrahman Farrag , Daehan Won , Sang Won Yoon
{"title":"Sim2Joint: Dynamic hybrid model for solder joint prediction across Sim2Real","authors":"Nieqing Cao , Jaewoo Kim , Abdelrahman Farrag , Daehan Won , Sang Won Yoon","doi":"10.1016/j.rcim.2024.102926","DOIUrl":"10.1016/j.rcim.2024.102926","url":null,"abstract":"<div><div>The objective of this research is to predict the solder joint’s fillet profile before its formation. Solder joints are crucial for the structural and operational reliability of electronic assemblies, yet their integrity can be compromised by defects such as cold joints, voids, or insufficient solder. Traditional physics-based simulations attempt to model these phenomena but often fall short due to simplifications that fail to capture real-world variability. Conversely, data-driven approaches leverage historical data from Surface Mount Technology (SMT) lines to predict joint quality, though their effectiveness can be hampered by data noise and imbalance. Addressing these limitations, this research introduces a hybrid modeling framework named Sim2Joint, which combines physics knowledge-based simulations with the adaptability of data-driven methods. By introducing Sim2Real in the joint simulation domain, Sim2Joint bridges the gap between simulation and real-world situations by integrating dynamic weights for printing and placing factors with real-world data, enhancing prediction accuracy and reliability. The framework also includes uncertainty quantification to provide more reliable solder joint fillet profile predictions, thereby enabling better decision-making and optimization in SMT processes. Sim2Joint is validated against various baselines, showcasing its capability to adapt to real-time changes and improve the predictive performance of solder joint quality assessments.</div></div>","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"93 ","pages":"Article 102926"},"PeriodicalIF":9.1,"publicationDate":"2024-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142816573","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}