样式: 排序: IF: - GO 导出 标记为已读
-
Multi-layer cutting path planning for composite enclosed cavity in additive and subtractive hybrid manufacturing Robot. Comput.-Integr. Manuf. (IF 9.1) Pub Date : 2024-07-11 Yin Wang, Yukai Chen, Yu Lu, Junyao Wang, Ke Huang, Bin Han, Qi Zhang
Additive and subtractive hybrid manufacturing (ASHM) refers to the hybrid manufacturing process where in-situ subtractive machining (SM) is introduced during additive manufacturing (AM). Its process characteristics dictate the necessity of planning multi-layer cutting paths in ASHM. Currently, the slice-based planning method cannot plan multi-axis cutting paths, and the machining accuracy is difficult
-
Computer-controlled 3D freeform surface weaving Robot. Comput.-Integr. Manuf. (IF 9.1) Pub Date : 2024-07-08 Xiangjia Chen, Lip M. Lai, Zishun Liu, Chengkai Dai, Isaac C.W. Leung, Charlie C.L. Wang, Yeung Yam
In this paper, we present a new computer-controlled weaving technology that enables the fabrication of woven structures in the shape of given 3D surfaces by using threads in non-traditional materials with high bending-stiffness, allowing for multiple applications with the resultant woven fabrics. A new weaving machine and a new manufacturing process are developed to realize the function of 3D surface
-
A sparse knowledge embedded configuration optimization method for robotic machining system toward improving machining quality Robot. Comput.-Integr. Manuf. (IF 9.1) Pub Date : 2024-07-08 Teng Zhang, Fangyu Peng, Xiaowei Tang, Rong Yan, Runpeng Deng, Shengqiang Zhao
In recent years, robotic machining has become one of the most important paradigms for the machining of large and complex parts due to the advantages of large workspaces and flexible configurations. However, different configurations will correspond to very different system performances, influenced by the position-dependent properties. Therefore, the configuration optimization of robotic machining system
-
MT-RSL: A multitasking-oriented robot skill learning framework based on continuous dynamic movement primitives for improving efficiency and quality in robot-based intelligent operation Robot. Comput.-Integr. Manuf. (IF 9.1) Pub Date : 2024-07-08 Yuming Ning, Tuanjie Li, Cong Yao, Wenqian Du, Yan Zhang, Yonghua Huang
Robot skill learning is one of the international advanced directions in the field of robot-based intelligent manufacturing, which makes it possible for robots to learn and operate autonomously in complex real-world environments. In this paper, we propose a multitasking-oriented robot skill learning framework named MT-RSL to improve the efficiency and robustness of multi-task robot skill learning in
-
Green and efficient-oriented human-robot hybrid partial destructive disassembly line balancing problem from non-disassemblability of components and noise pollution Robot. Comput.-Integr. Manuf. (IF 9.1) Pub Date : 2024-07-08 Lei Guo, Zeqiang Zhang, Tengfei Wu, Yu Zhang, Yanqing Zeng, Xinlan Xie
Current research on the disassembly line balancing problem ignores the influence of non-disassemblability of components. And this problem can lead to failure of the disassembly task, which can seriously affect the disassembly efficiency. This study integrates destructive operation into the human-robot disassembly line while considering noise. First, a mixed integer programming model is established
-
A methodology for information modelling and analysis of manufacturing processes for digital twins Robot. Comput.-Integr. Manuf. (IF 9.1) Pub Date : 2024-07-06 Shuo Su, Aydin Nassehi, Qunfen Qi, Ben Hicks
This paper introduces a methodology for information modelling and analysis of physical manufacturing processes for digital twins (DTs). It aims to establish a comprehensive and fundamental understanding of manufacturing processes regarding the specific purpose of the DT. Through this methodology, information entities within the manufacturing process that can be represented in DTs, along with their
-
Machining quality prediction of multi-feature parts using integrated multi-source domain dynamic adaptive transfer learning Robot. Comput.-Integr. Manuf. (IF 9.1) Pub Date : 2024-06-27 Pei Wang, Jingshuai Qi, Xun Xu, Sheng Yang
Machining quality prediction of multi-feature parts has been a challenging problem because of small dataset and inconsistent quality data distribution with respect to each machining feature. Transfer learning that leverages knowledge of one task and can be repurposed on another task seems a good solution for this purpose. However, traditional transfer learning typically has a single source domain and
-
Neural radiance fields in the industrial and robotics domain: Applications, research opportunities and use cases Robot. Comput.-Integr. Manuf. (IF 9.1) Pub Date : 2024-06-26 Eugen Šlapak, Enric Pardo, Matúš Dopiriak, Taras Maksymyuk, Juraj Gazda
The proliferation of technologies, such as extended reality (XR), has increased the demand for high-quality three-dimensional (3D) graphical representations. Industrial 3D applications encompass computer-aided design (CAD), finite element analysis (FEA), scanning, and robotics. However, current methods employed for industrial 3D representations suffer from high implementation costs and reliance on
-
Dynamic robot routing optimization: State–space decomposition for operations research-informed reinforcement learning Robot. Comput.-Integr. Manuf. (IF 9.1) Pub Date : 2024-06-25 Marlon Löppenberg, Steve Yuwono, Mochammad Rizky Diprasetya, Andreas Schwung
-
An overview of stiffening approaches for continuum robots Robot. Comput.-Integr. Manuf. (IF 9.1) Pub Date : 2024-06-25 Yeman Fan, Bowen Yi, Dikai Liu
Continuum robots have become more popular recently due to their scalable dexterity and mobility. However, they may suffer from issues like insufficient stiffness because they are designed to promote their flexibility. To address this issue and further improve their performance in all different application scenarios, stiffness flexibility is essential for this type of robot. Therefore, it is necessary
-
Hierarchical online automated planning for a flexible manufacturing system Robot. Comput.-Integr. Manuf. (IF 9.1) Pub Date : 2024-06-24 Xiaoting Dong, Guangxi Wan, Peng Zeng, Chunhe Song, Shijie Cui, Yiyang Liu
Task planning and action planning for workshop machines are essential for modern manufacturing. Traditionally, these two problems are solved independently with elaborate manual methods. However, personalized customization introduces more dynamic exogenous events into the manufacturing system, and it is then impossible to consider all possible dynamic scenarios manually. This paper focuses on online
-
Cloud-edge collaboration composition and scheduling for flexible manufacturing service with a multi-population co-evolutionary algorithm Robot. Comput.-Integr. Manuf. (IF 9.1) Pub Date : 2024-06-21 Weimin Jing, Yonghui Zhang, Youling Chen, Huan Zhang, Wen Huang
The Cloud Manufacturing Service Composition and Scheduling (CMfg-SCS) are essential processes in cloud manufacturing. Flexible Manufacturing Services (FMS), such as those provided by industrial robots, are widely used in cloud manufacturing to improve service quality and efficiency. Traditional CMfg-SCS methodologies, however, fall short in effectively managing the inherent temporal-dynamic QoS and
-
A novel method to enhance the accuracy of parameter identification in elasto-geometrical calibration for industrial robots Robot. Comput.-Integr. Manuf. (IF 9.1) Pub Date : 2024-06-20 Shihang Yu, Jie Nan, Yuwen Sun
Elasto-geometrical calibration is crucial for enhancing the absolute accuracy of robots in machining operations through the identification and compensation of parameter errors. However, the presence of inconsistent measurement units and improper selection of measuring poses can result in the ill-conditioned identification matrix (ICIM) issue, consequently impacting the accuracy of parameter identification
-
Online task allocation and scheduling in multi-manipulator system considering collision constraints and unknown tasks Robot. Comput.-Integr. Manuf. (IF 9.1) Pub Date : 2024-06-18 Xinyu Qin, Zixuan Liao, Chao Liu, Zhenhua Xiong
Compared to a single robot, multi-robot systems (MRS) offer several advantages in complex multi-task scenarios. The overall efficiency of MRS relies heavily on an efficient task allocation and scheduling process. Multi-robot task allocation (MRTA) is often formulated as a multiple traveling salesman problem, which is NP-hard and typically addressed offline. This paper specifically addresses the online
-
AEGLR-Net: Attention enhanced global–local refined network for accurate detection of car body surface defects Robot. Comput.-Integr. Manuf. (IF 9.1) Pub Date : 2024-06-17 Yike He, Baotong Wu, Xiao Liu, Baicun Wang, Jianzhong Fu, Songyu Hu
The complex background on the car body surface, such as the orange peel-like texture and shiny metallic powder, poses a considerable challenge to automated defect detection. Two mainstream methods are currently used to tackle this challenge: global information-based and attention mechanism-based methods. However, these methods lack the capability to integrate valuable global-to-local information and
-
Development of a new suction gripper for gripping under-constrained workpiece with minimized contact Robot. Comput.-Integr. Manuf. (IF 9.1) Pub Date : 2024-06-14 Kaige Shi, Xin Li
When gripping delicate workpieces such as a silicon wafer, contact should be minimized to protect the workpiece. Some existing suction grippers can grip a workpiece with only three contact points on its upper surface, which is minimal to fully constrain the workpiece. Further reducing the contact points will make the workpiece under-constrained and thus difficult to grip. This paper develops a new
-
Hybrid CNN-LSTM model driven image segmentation and roughness prediction for tool condition assessment with heterogeneous data Robot. Comput.-Integr. Manuf. (IF 9.1) Pub Date : 2024-06-08 Xu Zhu, Guilin Chen, Chao Ni, Xubin Lu, Jiang Guo
Worn tools might lead to substantial detrimental implications on the surface integrity of workpieces for precision/ultra-precision machining. Most previous research has heavily relied on singular information, which might not be appropriate enough to ascertain tool conditions and guarantee the accuracy of workpieces. This paper proposes a CNN-LSTM hybrid model directly utilizing tool images to predict
-
From cloud manufacturing to cloud–edge collaborative manufacturing Robot. Comput.-Integr. Manuf. (IF 9.1) Pub Date : 2024-06-08 Liang Guo, Yunlong He, Changcheng Wan, Yuantong Li, Longkun Luo
In recent years, the rapid development of information technology represented by the new generation of artificial intelligence has brought unprecedented impacts, challenges, and opportunities to the transformation of the manufacturing industry and the evolution of manufacturing models. In the past decade, a variety of new manufacturing systems and models have been proposed, with cloud manufacturing
-
A comprehensive review of robot intelligent grasping based on tactile perception Robot. Comput.-Integr. Manuf. (IF 9.1) Pub Date : 2024-06-07 Tong Li, Yuhang Yan, Chengshun Yu, Jing An, Yifan Wang, Gang Chen
The Advancements in tactile sensors and machine learning techniques open new opportunities for achieving intelligent grasping in robotics. Traditional robot is limited in its ability to perform autonomous grasping in unstructured environments. Although the existing robotic grasping method enhances the robot's understanding of its environment by incorporating visual perception, it still lacks the capability
-
Robot base position and spacecraft cabin angle optimization via homogeneous stiffness domain index with nonlinear stiffness characteristics Robot. Comput.-Integr. Manuf. (IF 9.1) Pub Date : 2024-06-04 Zhiqi Wang, Dong Gao, Kenan Deng, Yong Lu, Shoudong Ma, Jiao Zhao
The use of mobile robots for machining large components has received considerable research interest for the application of industrial robots in the machinery manufacturing sector. However, the low structural stiffness of industrial robots can result in poor machining quality under the action of cutting forces. Therefore, this paper proposes a simultaneous optimization method the mobile robot base position
-
Co2iAR: Co-located audio-visual enabled mobile collaborative industrial AR wiring harness assembly Robot. Comput.-Integr. Manuf. (IF 9.1) Pub Date : 2024-06-03 Wei Fang, Lixi Chen, Tienong Zhang, Hao Hu, Jiapeng Bi
Existing augmented reality (AR) assembly mainly provides visual instructions for operators from a first-person perspective, and it is hard to share individual working intents for co-located workers on the shop floor, especially for large-scale product assembly task that requires multiple operators working together. To bridge this gap for practical deployments, this paper proposes CoiAR, a co-located
-
Digital twin-driven dynamic scheduling for the assembly workshop of complex products with workers allocation Robot. Comput.-Integr. Manuf. (IF 9.1) Pub Date : 2024-05-25 Qinglin Gao, Jianhua Liu, Huiting Li, Cunbo Zhuang, Ziwen Liu
Assembly processes for complex products primarily involve manual assembly and often encounter various disruptive events, such as the insertion of new orders, order cancellations, task adjustments, workers absences, and job rotations. The dynamic scheduling problem for complex product assembly workshops requires consideration of trigger events and time nodes for rescheduling, as well as the allocations
-
Model-enabled robotic machining framework for repairing paint film defects Robot. Comput.-Integr. Manuf. (IF 9.1) Pub Date : 2024-05-23 Shengzhe Wang, Ziyan Xu, Yidan Wang, Ziyao Tan, Dahu Zhu
Region-based robotic machining is considered an effective strategy for automatically repairing paint film defects compared to conventional global machining. However, this process faces challenges due to irregularities in defect position, shape, and size. To overcome these challenges, this paper proposes a model-enabled robotic machining framework for repairing paint film defects by leveraging the workpiece
-
Research on human-robot interaction for robotic spatial 3D printing based on real-time hand gesture control Robot. Comput.-Integr. Manuf. (IF 9.1) Pub Date : 2024-05-22 Xinyu Shi, Chaoran Wang, Liyu Shi, Haining Zhou, Tyson Keen Phillips, Kang Bi, Weijiu Cui, Chengpeng Sun, Da Wan
With the rapid advancements in three-dimensional (3D) printing, researchers have shifted their focus towards the mechanical systems and methods used in this field. While Fused Deposition Modelling (FDM) remains the dominant method, alternative printing methods such as Spatial 3DP (S-3DP) have emerged. However, the majority of existing research on 3D printing technology has been emphasizing offline
-
Corrigendum to “Learning-based adaption of robotic friction models” [Robotics and Computer-Integrated Manufacturing Volume 89, October 2024] Robot. Comput.-Integr. Manuf. (IF 9.1) Pub Date : 2024-05-18 Philipp Scholl, Maged Iskandar, Sebastian Wolf, Jinoh Lee, Aras Bacho, Alexander Dietrich, Alin Albu-Schäffer, Gitta Kutyniok
-
Assembly complexity and physiological response in human-robot collaboration: Insights from a preliminary experimental analysis Robot. Comput.-Integr. Manuf. (IF 9.1) Pub Date : 2024-05-17 Matteo Capponi, Riccardo Gervasi, Luca Mastrogiacomo, Fiorenzo Franceschini
Industry 5.0 paradigm has renewed interest in the human sphere, emphasizing the importance of workers’ well-being in manufacturing activities. In such context, collaborative robotics originated as a technology to support humans in tiring and repetitive tasks. This study investigates the effects of assembly complexity in Human-Robot collaboration using physiological indicators of cognitive effort. In
-
Data-efficient multimodal human action recognition for proactive human–robot collaborative assembly: A cross-domain few-shot learning approach Robot. Comput.-Integr. Manuf. (IF 9.1) Pub Date : 2024-05-15 Tianyu Wang, Zhihao Liu, Lihui Wang, Mian Li, Xi Vincent Wang
With the recent vision of Industry 5.0, the cognitive capability of robots plays a crucial role in advancing proactive human–robot collaborative assembly. As a basis of the mutual empathy, the understanding of a human operator’s intention has been primarily studied through the technique of human action recognition. Existing deep learning-based methods demonstrate remarkable efficacy in handling information-rich
-
In-process 4D reconstruction in robotic additive manufacturing Robot. Comput.-Integr. Manuf. (IF 9.1) Pub Date : 2024-05-14 Sun Yeang Chew, Ehsan Asadi, Alejandro Vargas-Uscategui, Peter King, Subash Gautam, Alireza Bab-Hadiashar, Ivan Cole
Robotic additive manufacturing using a cold spray deposition head attached to a robotic arm can deposit material in a solid state with deposition rates in kilogrammes per hour. Under such a high deposition rate, the complicated interplay between the robot’s motion, gun standoff distance, spray angle, overlapping, and the interaction of supersonic powder particles with a growing structure could cause
-
Tabu search based on novel neighborhood structures for solving job shop scheduling problem integrating finite transportation resources Robot. Comput.-Integr. Manuf. (IF 9.1) Pub Date : 2024-05-14 Youjie Yao, Lin Gui, Xinyu Li, Liang Gao
As advancements in transportation equipment intelligence continue, the job shop scheduling problem integrating finite transportation resources (JSPIFTR) has attracted considerable attention. Within the domain of shop scheduling, the neighborhood structure serves as a cornerstone for enabling intelligent optimization algorithms to effectively navigate and discover optimal solutions. However, current
-
A whole-path posture optimization method of robotic grinding based on multi-performance evaluation indices Robot. Comput.-Integr. Manuf. (IF 9.1) Pub Date : 2024-05-13 Bing Chen, Yanan Wang, Shuhang Hu, Zhijian Tao, Junde Qi
Industrial robots are promising and competitive alternatives for performing machining operations due to their advantages of good mobility, high flexibility and low cost. However, the application of industrial robots in the field of high-precision machining such as grinding is hugely limited by the characteristic of weak stiffness. Aiming at this problem, a whole-path posture optimization method of
-
A framework for human–robot collaboration enhanced by preference learning and ergonomics Robot. Comput.-Integr. Manuf. (IF 9.1) Pub Date : 2024-05-13 Matteo Meregalli Falerni, Vincenzo Pomponi, Hamid Reza Karimi, Matteo Lavit Nicora, Le Anh Dao, Matteo Malosio, Loris Roveda
Industry 5.0 aims to prioritize human operators, focusing on their well-being and capabilities, while promoting collaboration between humans and robots to enhance efficiency and productivity. The integration of collaborative robots must ensure the health and well-being of human operators. Indeed, this paper addresses the need for a human-centered framework proposing a preference-based optimization
-
Corrigendum to ’In-situ Elastic Calibration of Robots: Minimally-Invasive Technology, Cover-Based Pose Search and Aerospace Case Studies’, Robotics and Computer-Integrated Manufacturing 89 (2024), 102743. Robot. Comput.-Integr. Manuf. (IF 9.1) Pub Date : 2024-05-06 Bruno Monsarrat, Julien-Mathieu Audet, Yves Fortin, Gabriel Côté, Michael Vistein, Lars Brandt, Ahmad Sadek, Florian Krebs
The authors provide a corrigendum for two equations of their published article [1]. These corrections do not impact the general kinetostatic model, elastic calibration algorithms, case studies’ results and conclusions presented in the article.
-
Leveraging digital twin into dynamic production scheduling: A review Robot. Comput.-Integr. Manuf. (IF 9.1) Pub Date : 2024-05-04 Nada Ouahabi, Ahmed Chebak, Oulaid Kamach, Oussama Laayati, Mourad Zegrari
The digital twin is an emerging technology that enhances industrial digitalization, as it establishes a dynamic virtual model that emulates a specific phenomenon of the corresponding physical system, thus imparting added value in many manufacturing activities. Production scheduling is one of the manufacturing activities that can fulfill step-improvements from the digital twin. However, modest endeavors
-
Learning-based adaption of robotic friction models Robot. Comput.-Integr. Manuf. (IF 9.1) Pub Date : 2024-05-01 Philipp Scholl, Maged Iskandar, Sebastian Wolf, Jinoh Lee, Aras Bacho, Alexander Dietrich, Alin Albu-Schäffer, Gitta Kutyniok
In the Fourth Industrial Revolution, wherein artificial intelligence and the automation of machines occupy a central role, the deployment of robots is indispensable. However, the manufacturing process using robots, especially in collaboration with humans, is highly intricate. In particular, modeling the friction torque in robotic joints is a longstanding problem due to the lack of a good mathematical
-
Privacy-preserving federated transfer learning for defect identification from highly imbalanced image data in additive manufacturing Robot. Comput.-Integr. Manuf. (IF 9.1) Pub Date : 2024-04-30 Jiafeng Tang, Zhibin Zhao, Yanjie Guo, Chenxi Wang, Xingwu Zhang, Ruqiang Yan, Xuefeng Chen
Defect identification is a crucial task for process monitoring and quality evaluation in additive manufacturing (AM). Deep learning (DL) has shown great potential for diverse fields, but some challenges have hindered the application in AM process monitoring. Firstly, DL-based methods are driven by big data and require a large number of training data. However, in reality, defective data is often rare
-
A novel model-based welding trajectory planning method for identical structural workpieces Robot. Comput.-Integr. Manuf. (IF 9.1) Pub Date : 2024-04-29 Weihua Fang, Xincheng Tian
Welding robots have been widely used with the development of manufacturing industry. At present, welding trajectory planning and programming of welding robots are performed separately for similar (structural) workpieces with different dimensions or deformations. Besides, the welding torch pose planning using conventional robot programming methods is time-consuming for workpieces with complex welding
-
A novel collision detection method based on current residuals for robots without joint torque sensors: A case study on UR10 robot Robot. Comput.-Integr. Manuf. (IF 9.1) Pub Date : 2024-04-27 Tian Xu, Hua Tuo, Qianqian Fang, Debin Shan, Hongzhe Jin, Jizhuang Fan, Yanhe Zhu, Jie Zhao
Existing model-based collision detection methods rely on accurate torque dynamic parameters identified using measured joint torques. However, for robots lacking joint torque sensors, only joint currents can be measured, and joint torques must be estimated through the linear relationship between joint currents and joint torque constants. This way can lead to cumulative identification errors in torque
-
Fusing LSTM neural network and expanded disturbance Kalman filter for estimating external disturbing forces of ball screw drives Robot. Comput.-Integr. Manuf. (IF 9.1) Pub Date : 2024-04-26 Yinghao Cheng, Yingguang Li, Ke Li, Xu Liu, Changqing Liu, Xiaozhong Hao
Monitoring external disturbing forces is of great significance for improving the control performance and interaction safety of ball screw drives. In consideration of the low cost in long-term use and the non-invasiveness to work space, estimating external disturbing forces using motor torque and motion states has been viewed as the solution that has great potential to be applied in real industry. However
-
Partially observable deep reinforcement learning for multi-agent strategy optimization of human-robot collaborative disassembly: A case of retired electric vehicle battery Robot. Comput.-Integr. Manuf. (IF 9.1) Pub Date : 2024-04-20 Jiaxu Gao, Guoxian Wang, Jinhua Xiao, Pai Zheng, Eujin Pei
The burgeoning electric vehicle (EV) industry has precipitated a commensurate surge in the consumption of EV batteries, which are currently labor-intensive and inefficient for the recycling and disassembly of EV batteries. However, it is a potential trend to enhance the efficacy and safety of the disassembly of EV batteries based on human-robot collaboration (HRC) method. Because of the uncertainty
-
Augmented reality spatial programming paradigm applied to end-user robot programming Robot. Comput.-Integr. Manuf. (IF 9.1) Pub Date : 2024-04-13 Michal Kapinus, Vítězslav Beran, Zdeněk Materna, Daniel Bambušek
-
An analytical tool path smoothing algorithm for robotic machining with the consideration of redundant kinematics Robot. Comput.-Integr. Manuf. (IF 9.1) Pub Date : 2024-04-10 Jixiang Yang, Qi Qi, Abulikemu Adili, Han Ding
In the machining of complex parts with free-formed surfaces, robots are widely employed due to their advantages of a large operating space and high flexibility. The industrial robot with 6 degrees-of-freedom (DOF) has an extra redundant degree of freedom around the tool axis, which does not affect the tool pose related to the workpieces but influences the robot's joint configuration. The motion performance
-
Research on trajectory learning and modification method based on improved dynamic movement primitives Robot. Comput.-Integr. Manuf. (IF 9.1) Pub Date : 2024-04-09 Nanyan Shen, Jiawei Mao, Jing Li, Zhengquan Mao
Traditional robot trajectory planning and programming methods often struggle to adapt to changing working requirements, leading to repeated programming in manufacturing processes. To address these challenges, a trajectory learning and modification method based on improved Dynamic Movement Primitives (DMPs), called FDC-DMP, is proposed. The method introduces an improved force-controlled dynamic coupling
-
Seam tracking and gap bridging during robotic laser beam welding via grayscale imaging and wobbling Robot. Comput.-Integr. Manuf. (IF 9.1) Pub Date : 2024-04-08 Davide Maria Boldrin, Lorenzo Molinari Tosatti, Barbara Previtali, Ali Gökhan Demir
-
Exploring the synergies between collaborative robotics, digital twins, augmentation, and industry 5.0 for smart manufacturing: A state-of-the-art review Robot. Comput.-Integr. Manuf. (IF 9.1) Pub Date : 2024-04-06 Muhammad Hamza Zafar, Even Falkenberg Langås, Filippo Sanfilippo
Industry 5.0 aims at establishing an inclusive, smart and sustainable production process that encourages human creativity and expertise by leveraging enhanced automation and machine intelligence. Collaborative robotics, or “cobotics”,is a major enabling technology of Industry 5.0, which aspires at improving human dexterity by elevating robots to extensions of human capabilities and, ultimately, even
-
Quantification of uncertainty in robot pose errors and calibration of reliable compensation values Robot. Comput.-Integr. Manuf. (IF 9.1) Pub Date : 2024-04-05 Teng Zhang, Fangyu Peng, Rong Yan, Xiaowei Tang, Runpeng Deng, Jiangmiao Yuan
-
Accurate error compensation method for multi-axis parallel machine via singularized jacobi geometric parameter correction and coupling error evaluation Robot. Comput.-Integr. Manuf. (IF 9.1) Pub Date : 2024-04-03 Yuheng Luo, Jian Gao, Disai Chen, Lanyu Zhang, Yachao Liu, Yongbin Zhong
-
Progress, challenges and trends on vision sensing technologies in automatic/intelligent robotic welding: State-of-the-art review Robot. Comput.-Integr. Manuf. (IF 9.1) Pub Date : 2024-03-27 Qiang Guo, Zi Yang, Jinting Xu, Yan Jiang, Wenbo Wang, Zonglin Liu, Weisen Zhao, Yuwen Sun
Welding is a method of realizing material connections, and the development of modern sensing technology is pushing this traditional process towards automation and intelligence. Among many sensing methods, visual sensing stands out with its advantages of non-contact, fast response and economic benefits, etc. This paper provides a comprehensive review of visualization methods in the context of specific
-
An Expandable and Generalized Method for Equipment Information Reflection in Digital Twin Workshop Systems Robot. Comput.-Integr. Manuf. (IF 9.1) Pub Date : 2024-03-27 Yueze Zhang, Dongjie Zhang, Jun Yan, Zhifeng Liu, Tongtong Jin
A production workshop is equipped with diverse equipment and machinery, and manufacturing data generated by different equipment show certain differences. Therefore, developing a method with an information presentation capability for a digital twin workshop system (DTWS) can be challenging due to the numerous information sources and types. The level of detail provided for a DTWS is directly related
-
Digital twin enhanced quality prediction method of powder compaction process Robot. Comput.-Integr. Manuf. (IF 9.1) Pub Date : 2024-03-26 Ying Zuo, Hujie You, Xiaofu Zou, Wei Ji, Fei Tao
During the powder compaction process, process parameters are required for product quality prediction. However, the inadequacy of compaction data leads to difficulties in constructing models for quality prediction. Meanwhile, the existing data generation methods can only generate required data partially, and fail to generate data for extreme operating conditions and difficult-to-measure quality parameters
-
A general energy modeling network for serial industrial robots integrating physical mechanism priors Robot. Comput.-Integr. Manuf. (IF 9.1) Pub Date : 2024-03-25 Ming Yao, Xiang Zhou, Zhufeng Shao, Liping Wang
Industrial robots (IRs), as the core equipment of intelligent manufacturing, play increasingly important roles in various industrial scenarios such as assembly, welding, handling, and spraying, significantly improving production efficiency and product quality. The massive popularization and application of IRs have brought about a sharp increase in energy consumption (EC), and the modeling and optimization
-
An ontology and rule-based method for human–robot collaborative disassembly planning in smart remanufacturing Robot. Comput.-Integr. Manuf. (IF 9.1) Pub Date : 2024-03-20 Youxi Hu, Chao Liu, Ming Zhang, Yuqian Lu, Yu Jia, Yuchun Xu
Disassembly is a decisive step in the remanufacturing process of End-of-Life (EoL) products. As an emerging semi-automatic disassembly paradigm, human–robot collaborative disassembly (HRCD) offers multiple disassembly methods to enhance flexibility and efficiency. However, HRCD increases the complexity of planning and determining the optimal disassembly sequence and scheme. Currently, the optimisation
-
A dual-robot cooperative arc welding path planning algorithm based on multi-objective cross-entropy optimization Robot. Comput.-Integr. Manuf. (IF 9.1) Pub Date : 2024-03-19 Qichao Tang, Lei Ma, Duo Zhao, Yongkui Sun, Jieyu Lei, Qingyi Wang
In this paper a novel discrete multi-objective cross-entropy optimization (CrMOCEO) algorithm is proposed to solve the path planning problem of dual-robot cooperative arc welding. We strive to find a low-cost, fast and more efficient solution for robotic welding of large complex components. Firstly, an optimization model of dual-robot welding path planning is established by considering various variables
-
Towards industry 5.0 through metaverse Robot. Comput.-Integr. Manuf. (IF 9.1) Pub Date : 2024-03-18 Alberto Martínez-Gutiérrez, Javier Díez-González, Hilde Perez, Madalena Araújo
The digital transformation of the industry allows the optimization of resources through enabling technology that virtualizes the behavior of Cyber-Physical Systems (CPS) along the entire value chain. However, these virtual environments characterized by machine-to-machine interactions lacked the presence of humans who are at the center of the next defined industrial revolution, Industry 5.0. The goal
-
In-situ elastic calibration of robots: Minimally-invasive technology, cover-based pose search and aerospace case studies Robot. Comput.-Integr. Manuf. (IF 9.1) Pub Date : 2024-03-16 Bruno Monsarrat, Julien-Mathieu Audet, Yves Fortin, Gabriel Côté, Michael Vistein, Lars Brandt, Ahmad Sadek, Florian Krebs
-
End-of-life electric vehicle battery disassembly enabled by intelligent and human-robot collaboration technologies: A review Robot. Comput.-Integr. Manuf. (IF 9.1) Pub Date : 2024-03-15 Weidong Li, Yiqun Peng, Yu Zhu, Duc Truong Pham, A.Y.C. Nee, S.K. Ong
Electric vehicles (EVs) have been experiencing radical growth to embrace the ambitious targets of decarbonisation and circular economies. The trend has led to a significant surge in the number of lithium-ion batteries (LIBs) that will soon reach the end-of-life (EoL) stage. Given that landfilling EoL EV LIBs generates substantially negative impacts on the environment, it is imperative to develop economically
-
Tool path correction for robotic deburring using local non-rigid 3D registration Robot. Comput.-Integr. Manuf. (IF 9.1) Pub Date : 2024-03-13 Peiyang Peng, Chengxing Wu, Jixiang Yang, Han Ding
The presence of residual burrs on the surface of workpieces not only affects the surface quality but also reduces their performance. The position and orientation of the cutting tool in the deburring process are crucial for effective burr removal. Due to the interference caused by the burrs uncertainty or the manufacturing deformation, the off-line path from the workpiece CAD model is difficult to ensure
-
A milling test-based coordinate calibration approach for the dual-robot mirror milling system with a measurement module Robot. Comput.-Integr. Manuf. (IF 9.1) Pub Date : 2024-03-10 Yang Zhang, Peng Guo, Nuodi Huang, Yaqi Zhang, Limin Zhu
Accurate collaborative positioning by dual robots is crucial for achieving high precision in dual-robot mirror milling operations. However, the tool frames constructed in conventional dual-robot coordinate calibration approaches need to be substituted by a new set designated for the mirror milling, which may induce a notable reduction of collaborative positioning accuracy. This paper presents a novel
-
Integration of an exoskeleton robotic system into a digital twin for industrial manufacturing applications Robot. Comput.-Integr. Manuf. (IF 9.1) Pub Date : 2024-03-10 Hoonmin Park, Minchul Shin, Gyubok Choi, Yuseop Sim, Jiho Lee, Huitaek Yun, Martin Byung-Guk Jun, Gyuman Kim, Younghun Jeong, Hak Yi
Industry 4.0 has underscored the importance of human–robot collaboration (HRC), necessitating an efficient integration of human workers and robots to achieve high-productivity manufacturing. Traditional HRC-related teaching operations rely on intuitive tools, such as a teach pendant, but are effort-intensive and require personnel with specialized skills, particularly those who use collaborative robots
-
Design and implementation of a precision levelling composite stage with active passive vibration isolation Robot. Comput.-Integr. Manuf. (IF 9.1) Pub Date : 2024-03-06 Lanyu Zhang, Shaoxuan Zhang, Jian Gao, Junhao Yi, Hao Wen, Yun Chen, Xin Chen
-
Sensorless admittance control of 6-DoF parallel robot in human-robot collaborative assembly Robot. Comput.-Integr. Manuf. (IF 9.1) Pub Date : 2024-03-05 Tao Sun, Jiarui Sun, Binbin Lian, Qi Li
This paper presents an adaptive admittance control to achieve human-robot collaborative (HRC) assembling of large, heavy components without using external sensors. This sensorless adaptive admittance control is constructed by the dynamic model of a six degree-of-freedom (DoF) parallel robot based on finite and instantaneous screw (FIS) theory. The dynamic model is intuitive and easy to be programmed