Robotics and Computer-integrated Manufacturing最新文献

Towards safe motion planning for industrial human-robot interaction: A co-evolution approach based on human digital twin and mixed reality

IF 9.1 1区计算机科学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Robotics and Computer-integrated Manufacturing

Pub Date : 2025-03-06 DOI: 10.1016/j.rcim.2025.103012

Bohan Feng, Zeqing Wang, Lianjie Yuan, Qi Zhou, Yulin Chen, Youyi Bi

Advanced human-robot interaction (HRI) is essential for the next-generation human-centric manufacturing mode such as “Industry 5.0”. Despite recent mutual cognitive approaches can enhance the understanding and collaboration between humans and robots, these methods often rely on predefined rules and are limited in adapting to new tasks or changes of the working environment. These limitations can hinder the popularization of collaborative robots in dynamic manufacturing environments, where tasks can be highly variable, and unforeseen operational changes frequently occur. To address these challenges, we propose a co-evolution approach for the safe motion planning of industrial human-robot interaction. The core idea is to promote the evolution of human worker’s safe operation cognition as well as the evolution of robot’s safe motion planning strategy in a unified and continuous framework by leveraging human digital twin (HDT) and mixed reality (MR) technologies. Specifically, HDT captures real-time human behaviors and postures, which enables robots to adapt dynamically to the changes of human behavior and environment. HDT also refines deep reinforcement learning (DRL)-based motion planning, allowing robots to continuously learn from human actions and update their motion strategies. On the other hand, MR superimposes rich information regarding the tasks and robot in the physical world, helping human workers better understand and adapt to robot’s actions. MR also provides intuitive gesture-based user interface, further improving the smoothness of human-robot interaction. We validate the proposed approach’s effectiveness with evaluations in realistic manufacturing scenarios, demonstrating its potential to advance HRI practice in the context of smart manufacturing.

{"title":"Towards safe motion planning for industrial human-robot interaction: A co-evolution approach based on human digital twin and mixed reality","authors":"Bohan Feng, Zeqing Wang, Lianjie Yuan, Qi Zhou, Yulin Chen, Youyi Bi","doi":"10.1016/j.rcim.2025.103012","DOIUrl":"10.1016/j.rcim.2025.103012","url":null,"abstract":"<div><div>Advanced human-robot interaction (HRI) is essential for the next-generation human-centric manufacturing mode such as “Industry 5.0”. Despite recent mutual cognitive approaches can enhance the understanding and collaboration between humans and robots, these methods often rely on predefined rules and are limited in adapting to new tasks or changes of the working environment. These limitations can hinder the popularization of collaborative robots in dynamic manufacturing environments, where tasks can be highly variable, and unforeseen operational changes frequently occur. To address these challenges, we propose a co-evolution approach for the safe motion planning of industrial human-robot interaction. The core idea is to promote the evolution of human worker’s safe operation cognition as well as the evolution of robot’s safe motion planning strategy in a unified and continuous framework by leveraging human digital twin (HDT) and mixed reality (MR) technologies. Specifically, HDT captures real-time human behaviors and postures, which enables robots to adapt dynamically to the changes of human behavior and environment. HDT also refines deep reinforcement learning (DRL)-based motion planning, allowing robots to continuously learn from human actions and update their motion strategies. On the other hand, MR superimposes rich information regarding the tasks and robot in the physical world, helping human workers better understand and adapt to robot’s actions. MR also provides intuitive gesture-based user interface, further improving the smoothness of human-robot interaction. We validate the proposed approach’s effectiveness with evaluations in realistic manufacturing scenarios, demonstrating its potential to advance HRI practice in the context of smart manufacturing.</div></div>","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"95 ","pages":"Article 103012"},"PeriodicalIF":9.1,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143547999","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}

引用次数: 0

Transfer learning and augmented data-driven parameter prediction for robotic welding 用于机器人焊接的迁移学习和增强型数据驱动参数预测

IF 9.1 1区计算机科学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Robotics and Computer-integrated Manufacturing

Pub Date : 2025-03-06 DOI: 10.1016/j.rcim.2025.102992

Cheng Zhang , Yingfeng Zhang , Sichao Liu , Lihui Wang

Robotic welding envisioned for the future of factories will promote high-demanding and customised tasks with overall higher productivity and quality. Within the context, robotic welding parameter prediction is essential for maintaining high standards of quality, efficiency, safety, and cost-effectiveness in smart manufacturing. However, data acquisition of welding process parameters is limited by process libraries and small sample sizes, given complex welding working environments, and it also requires extensive and costly experimentation. To address these issues, this study proposes a transfer learning and augmented data-driven approach for high-accuracy prediction of robotic welding parameters. Firstly, a data space transfer method is developed to construct a domain adaptation mapping matrix, focusing on small sample welding process parameters, and a data augmentation method is adopted to transfer welding process parameters with augmented sample data. Then, a DST-Multi-XGBoost model is developed to establish a mapping relationship between welding task features and welding process parameters. The constructed model can consider the relationship between the output, which reduces the complexity of the model and the number of parameters. Even with a small initial sample size, the model can use augmented data to understand complex coupling relationships and accurately predict welding process parameters. Finally, the effectiveness of the developed approach has been experimentally validated by a case study of robotic welding.

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引用次数: 0

A dual-arm robotic cooperative framework for multiple peg-in-hole assembly of large objects

IF 9.1 1区计算机科学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Robotics and Computer-integrated Manufacturing

Pub Date : 2025-02-27 DOI: 10.1016/j.rcim.2025.102991

Dongsheng Ge, Huan Zhao, Dianxi Li, Dongchen Han, Xiangfei Li, Jiexin Zhang, Han Ding

Single peg-in-hole assembly of small objects has been researched extensively. However, these studies limit applicability to multiple peg-in-hole assembly of large objects, due to the complex contact state, and the large size and weight of the objects. To address these challenges, this paper proposes a dual-arm cooperative multiple peg-in-hole assembly framework (DAC-MPiH) for large objects, leveraging the capabilities of dual robots to manage larger, heavier objects. The DAC-MPiH framework comprises three key components: dual-arm force/position coordination, external force/torque estimation, and an eight-stage assembly strategy. The proposed framework integrates a compliant dynamical system (CDS) into both inner and outer control loops, ensuring robust force/position coordination and stable manipulation at the object level. The framework introduces an object parameter estimation method based on a virtual center of mass and least squares to enhance the accuracy of external force/torque estimation. The assembly strategy includes four preparation stages and four assembly stages, utilizing a CDS-based variable impedance and variable reference force controller for stable adjusting, and a hybrid force/position controller for efficient rotating. Experiments were conducted on a dual-arm robotic platform, and the results demonstrate the effectiveness of the proposed method in achieving stable and efficient multiple peg-in-hole assembly of large objects.

{"title":"A dual-arm robotic cooperative framework for multiple peg-in-hole assembly of large objects","authors":"Dongsheng Ge, Huan Zhao, Dianxi Li, Dongchen Han, Xiangfei Li, Jiexin Zhang, Han Ding","doi":"10.1016/j.rcim.2025.102991","DOIUrl":"10.1016/j.rcim.2025.102991","url":null,"abstract":"<div><div>Single peg-in-hole assembly of small objects has been researched extensively. However, these studies limit applicability to multiple peg-in-hole assembly of large objects, due to the complex contact state, and the large size and weight of the objects. To address these challenges, this paper proposes a dual-arm cooperative multiple peg-in-hole assembly framework (DAC-MPiH) for large objects, leveraging the capabilities of dual robots to manage larger, heavier objects. The DAC-MPiH framework comprises three key components: dual-arm force/position coordination, external force/torque estimation, and an eight-stage assembly strategy. The proposed framework integrates a compliant dynamical system (CDS) into both inner and outer control loops, ensuring robust force/position coordination and stable manipulation at the object level. The framework introduces an object parameter estimation method based on a virtual center of mass and least squares to enhance the accuracy of external force/torque estimation. The assembly strategy includes four preparation stages and four assembly stages, utilizing a CDS-based variable impedance and variable reference force controller for stable adjusting, and a hybrid force/position controller for efficient rotating. Experiments were conducted on a dual-arm robotic platform, and the results demonstrate the effectiveness of the proposed method in achieving stable and efficient multiple peg-in-hole assembly of large objects.</div></div>","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"95 ","pages":"Article 102991"},"PeriodicalIF":9.1,"publicationDate":"2025-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143508188","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}

引用次数: 0

Digital twin-enabled robotics for smart tag deployment and sensing in confined space

IF 9.1 1区计算机科学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Robotics and Computer-integrated Manufacturing

Pub Date : 2025-02-24 DOI: 10.1016/j.rcim.2025.102993

Alan Putranto , Tzu-Hsuan Lin , Ping-Ting Tsai

The deployment of smart sensors in confined spaces presents significant challenges due to limited visibility, environmental constraints, and communication interference. This study introduces a novel integration of digital twin technology with robotics to address these challenges, enabling precise and reliable sensor deployment in complex environments such as steel box girders. The proposed system leverages a digital twin framework for real-time simulation, calibration, and monitoring, ensuring spatial consistency between virtual and physical operations. Advanced calibration methods align the robotic arm with its 3D camera coordinates, enhancing deployment accuracy. Communication robustness is achieved by strategically prioritizing critical control and sensor signals, mitigating the impact of wireless interference in confined spaces. Additionally, the system automates the deployment of RFID-based smart sensors, incorporating 3D-printed protective casings for durability in harsh conditions. Experimental results demonstrate the system's effectiveness in overcoming spatial, visibility, and communication challenges, providing a scalable solution for structural health monitoring and other industrial applications. This study contributes a holistic and innovative robotics and digital twin integration framework in confined and complex environments.

{"title":"Digital twin-enabled robotics for smart tag deployment and sensing in confined space","authors":"Alan Putranto , Tzu-Hsuan Lin , Ping-Ting Tsai","doi":"10.1016/j.rcim.2025.102993","DOIUrl":"10.1016/j.rcim.2025.102993","url":null,"abstract":"<div><div>The deployment of smart sensors in confined spaces presents significant challenges due to limited visibility, environmental constraints, and communication interference. This study introduces a novel integration of digital twin technology with robotics to address these challenges, enabling precise and reliable sensor deployment in complex environments such as steel box girders. The proposed system leverages a digital twin framework for real-time simulation, calibration, and monitoring, ensuring spatial consistency between virtual and physical operations. Advanced calibration methods align the robotic arm with its 3D camera coordinates, enhancing deployment accuracy. Communication robustness is achieved by strategically prioritizing critical control and sensor signals, mitigating the impact of wireless interference in confined spaces. Additionally, the system automates the deployment of RFID-based smart sensors, incorporating 3D-printed protective casings for durability in harsh conditions. Experimental results demonstrate the system's effectiveness in overcoming spatial, visibility, and communication challenges, providing a scalable solution for structural health monitoring and other industrial applications. This study contributes a holistic and innovative robotics and digital twin integration framework in confined and complex environments.</div></div>","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"95 ","pages":"Article 102993"},"PeriodicalIF":9.1,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143474751","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}

引用次数: 0

Feedrate scheduling method for 3-PRS hybrid machine tools considering kinematic constraints

IF 9.1 1区计算机科学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Robotics and Computer-integrated Manufacturing

Pub Date : 2025-02-22 DOI: 10.1016/j.rcim.2025.102988

Haiming Zhang , Jianzhong Yang , Song Gao , Xiumei Gong , Wanqiang Zhu

Hybrid machine tools (HMTs), known for their fast response speed, high stiffness, and accuracy, have found wide applications in aerospace and other industries. However, maintaining stability and durability during high-speed machining necessitates careful feedrate scheduling. This study introduces a novel feedrate scheduling method for 3-prismatic-revolute-spherical (3-PRS) HMTs, ensuring that the velocities and accelerations of the drive axes remain within predefined ranges. Initially, the velocity and acceleration dynamics of the 3-PRS mechanism were scrutinized using the screw theory. Subsequently, a virtual axis programming method was introduced, transforming the HMT into a virtual double-pendulum five-axis serial machine tool. In addition, the space of the master–slave movement (SMM) concept is proposed to define the toolpath. Moreover, a strategy for constraining the tool center point rate and acceleration was devised based on the kinematic relationships between the drive axes, virtual axes, and tool center points. Simulation and experiment validated the efficacy of the feedrate scheduling method, demonstrating compliance with the kinematic constraints of the drive axes and enhanced machining efficiency.

{"title":"Feedrate scheduling method for 3-PRS hybrid machine tools considering kinematic constraints","authors":"Haiming Zhang , Jianzhong Yang , Song Gao , Xiumei Gong , Wanqiang Zhu","doi":"10.1016/j.rcim.2025.102988","DOIUrl":"10.1016/j.rcim.2025.102988","url":null,"abstract":"<div><div>Hybrid machine tools (HMTs), known for their fast response speed, high stiffness, and accuracy, have found wide applications in aerospace and other industries. However, maintaining stability and durability during high-speed machining necessitates careful feedrate scheduling. This study introduces a novel feedrate scheduling method for 3-prismatic-revolute-spherical (3-PRS) HMTs, ensuring that the velocities and accelerations of the drive axes remain within predefined ranges. Initially, the velocity and acceleration dynamics of the 3-PRS mechanism were scrutinized using the screw theory. Subsequently, a virtual axis programming method was introduced, transforming the HMT into a virtual double-pendulum five-axis serial machine tool. In addition, the space of the master–slave movement (SMM) concept is proposed to define the toolpath. Moreover, a strategy for constraining the tool center point rate and acceleration was devised based on the kinematic relationships between the drive axes, virtual axes, and tool center points. Simulation and experiment validated the efficacy of the feedrate scheduling method, demonstrating compliance with the kinematic constraints of the drive axes and enhanced machining efficiency.</div></div>","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"95 ","pages":"Article 102988"},"PeriodicalIF":9.1,"publicationDate":"2025-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143465411","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}

引用次数: 0

A novel weld seam extraction method with semantic segmentation and point cloud feature for irregular structure workpieces

IF 9.1 1区计算机科学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Robotics and Computer-integrated Manufacturing

Pub Date : 2025-02-21 DOI: 10.1016/j.rcim.2025.102987

Yuankai Zhang , Yusen Geng , Xincheng Tian , Yujie Sun , Xiaolong Xu

The intricate surfaces of irregular structure workpieces present significant challenges for robotic welding path planning. To facilitate robot welding without teaching and programming, this paper proposes a weld seam extraction method that integrates semantic segmentation with point cloud features. This approach effectively harnesses the RGB-D information captured by an area array structured light camera. Initially, the K-Net model is employed for semantic segmentation of the workpiece using two-dimensional image features. This segmentation facilitates the coarse localization of the weld seam by extracting edges based on the segmented image mask, thus setting the stage for detailed weld seam extraction using point cloud features. Subsequent improvements in the DLP structured light vision imaging process allow for accurate edge point cloud reconstruction and adaptive extraction of ROI based on shape extension. The extraction of weld seam feature points is then performed using the LOBB feature extraction method, followed by a polynomial fitting of the weld seam using a least-squares approach. Experimental results indicate that the maximum error in weld seam extraction is less than 1.2 mm, with a root mean square error of less than 0.7 mm, and the algorithm completes its task in under 5 s, demonstrating the method’s efficiency and precision.

{"title":"A novel weld seam extraction method with semantic segmentation and point cloud feature for irregular structure workpieces","authors":"Yuankai Zhang , Yusen Geng , Xincheng Tian , Yujie Sun , Xiaolong Xu","doi":"10.1016/j.rcim.2025.102987","DOIUrl":"10.1016/j.rcim.2025.102987","url":null,"abstract":"<div><div>The intricate surfaces of irregular structure workpieces present significant challenges for robotic welding path planning. To facilitate robot welding without teaching and programming, this paper proposes a weld seam extraction method that integrates semantic segmentation with point cloud features. This approach effectively harnesses the RGB-D information captured by an area array structured light camera. Initially, the K-Net model is employed for semantic segmentation of the workpiece using two-dimensional image features. This segmentation facilitates the coarse localization of the weld seam by extracting edges based on the segmented image mask, thus setting the stage for detailed weld seam extraction using point cloud features. Subsequent improvements in the DLP structured light vision imaging process allow for accurate edge point cloud reconstruction and adaptive extraction of ROI based on shape extension. The extraction of weld seam feature points is then performed using the LOBB feature extraction method, followed by a polynomial fitting of the weld seam using a least-squares approach. Experimental results indicate that the maximum error in weld seam extraction is less than 1.2 mm, with a root mean square error of less than 0.7 mm, and the algorithm completes its task in under 5 s, demonstrating the method’s efficiency and precision.</div></div>","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"95 ","pages":"Article 102987"},"PeriodicalIF":9.1,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143452841","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}

引用次数: 0

A disjunctive graph-based metaheuristic for flexible job-shop scheduling problems considering fixture shortages in customized manufacturing systems

IF 9.1 1区计算机科学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Robotics and Computer-integrated Manufacturing

Pub Date : 2025-02-20 DOI: 10.1016/j.rcim.2025.102981

Jiahang Li , Qihao Liu , Cuiyu Wang , Xinyu Li

Customized manufacturing systems represent a promising production paradigm capable of producing a variety of products to meet diverse customer needs. However, limited resources and complex processes complicate the optimization of production scheduling and resource allocation. In particular, fixture shortages frequently arise in a highly customized manufacturing enterprise, as multiple new jobs may require the same fixture simultaneously. Consequently, certain fixtures must be machined as part of production tasks in workshops. To derive high-quality scheduling solutions, this paper proposes an improved genetic algorithm with a disjunctive graph-based local search for flexible job-shop scheduling problems considering on-site machining fixtures. First, several problem-specific genetic operators are introduced to enhance exploration capabilities. Second, a disjunctive graph for total weighted tardiness is established to identify critical paths. Third, a critical path-based local search method is proposed, incorporating three knowledge-based neighborhood structures to improve exploitation capabilities. Finally, the proposed algorithm is evaluated in 20 instances and compared against five state-of-the-art algorithms. The experimental results demonstrate that the proposed algorithm significantly outperforms its competitors regarding convergence and statistical metrics. A daily order from the enterprise is examined as a case study to evaluate the practical benefits of the proposed algorithm. From this case study, the total weighted tardiness and makespan are reduced by 62.71% and 42.13%, respectively, compared to the original scheduling solution.

{"title":"A disjunctive graph-based metaheuristic for flexible job-shop scheduling problems considering fixture shortages in customized manufacturing systems","authors":"Jiahang Li , Qihao Liu , Cuiyu Wang , Xinyu Li","doi":"10.1016/j.rcim.2025.102981","DOIUrl":"10.1016/j.rcim.2025.102981","url":null,"abstract":"<div><div>Customized manufacturing systems represent a promising production paradigm capable of producing a variety of products to meet diverse customer needs. However, limited resources and complex processes complicate the optimization of production scheduling and resource allocation. In particular, fixture shortages frequently arise in a highly customized manufacturing enterprise, as multiple new jobs may require the same fixture simultaneously. Consequently, certain fixtures must be machined as part of production tasks in workshops. To derive high-quality scheduling solutions, this paper proposes an improved genetic algorithm with a disjunctive graph-based local search for flexible job-shop scheduling problems considering on-site machining fixtures. First, several problem-specific genetic operators are introduced to enhance exploration capabilities. Second, a disjunctive graph for total weighted tardiness is established to identify critical paths. Third, a critical path-based local search method is proposed, incorporating three knowledge-based neighborhood structures to improve exploitation capabilities. Finally, the proposed algorithm is evaluated in 20 instances and compared against five state-of-the-art algorithms. The experimental results demonstrate that the proposed algorithm significantly outperforms its competitors regarding convergence and statistical metrics. A daily order from the enterprise is examined as a case study to evaluate the practical benefits of the proposed algorithm. From this case study, the total weighted tardiness and makespan are reduced by 62.71% and 42.13%, respectively, compared to the original scheduling solution.</div></div>","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"95 ","pages":"Article 102981"},"PeriodicalIF":9.1,"publicationDate":"2025-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143452840","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}

引用次数: 0

Streamlined robotic hand–eye calibration of multiple 2D-profilers: A rapid, closed-form two-stage method via a single-plane artefact

IF 9.1 1区计算机科学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Robotics and Computer-integrated Manufacturing

Pub Date : 2025-02-19 DOI: 10.1016/j.rcim.2025.102984

Subash Gautam , Hans Lohr , Alejandro Vargas-Uscategui , Peter C King , Alireza Bab-Hadiashar , Ivan Cole , Ehsan Asadi

A 2D laser profiler is commonly utilized in high-precision robotic settings to capture detailed surface profiles for 3D scanning. By collecting and combining numerous such measurements from different viewpoints, it is possible to assemble a comprehensive 3D map. However, to effectively merge these individual 2D profiles into a singular global framework, the spatial relationship between the scanners and the robot’s reference frame is required. Traditional hand–eye calibration techniques typically necessitate specific calibration artifacts or extraneous positional sensors, and the process is either manually executed or only partially automated, demanding considerable time and effort. This paper introduces an innovative, closed-form approach to hand–eye calibration that can be applied to a single scanner or an array of multiple scanners. Our method circumvents the requirements for initial parameter estimates or specialized calibration implements, instead employing a flat plane for hand–eye calibration. This method paves the way for a fully automated calibration sequence comprising only three rotational and three translational poses, reducing the total calibration duration. This streamlined process has undergone strict experimental validation utilizing a calibrated sphere, proving its effectiveness not only with a solitary scanner setup but also with an ensemble of three scanners.

{"title":"Streamlined robotic hand–eye calibration of multiple 2D-profilers: A rapid, closed-form two-stage method via a single-plane artefact","authors":"Subash Gautam , Hans Lohr , Alejandro Vargas-Uscategui , Peter C King , Alireza Bab-Hadiashar , Ivan Cole , Ehsan Asadi","doi":"10.1016/j.rcim.2025.102984","DOIUrl":"10.1016/j.rcim.2025.102984","url":null,"abstract":"<div><div>A 2D laser profiler is commonly utilized in high-precision robotic settings to capture detailed surface profiles for 3D scanning. By collecting and combining numerous such measurements from different viewpoints, it is possible to assemble a comprehensive 3D map. However, to effectively merge these individual 2D profiles into a singular global framework, the spatial relationship between the scanners and the robot’s reference frame is required. Traditional hand–eye calibration techniques typically necessitate specific calibration artifacts or extraneous positional sensors, and the process is either manually executed or only partially automated, demanding considerable time and effort. This paper introduces an innovative, closed-form approach to hand–eye calibration that can be applied to a single scanner or an array of multiple scanners. Our method circumvents the requirements for initial parameter estimates or specialized calibration implements, instead employing a flat plane for hand–eye calibration. This method paves the way for a fully automated calibration sequence comprising only three rotational and three translational poses, reducing the total calibration duration. This streamlined process has undergone strict experimental validation utilizing a calibrated sphere, proving its effectiveness not only with a solitary scanner setup but also with an ensemble of three scanners.</div></div>","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"95 ","pages":"Article 102984"},"PeriodicalIF":9.1,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143444818","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}

引用次数: 0

Reinforcement Learning-based five-axis continuous inspection method for complex freeform surface

IF 9.1 1区计算机科学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Robotics and Computer-integrated Manufacturing

Pub Date : 2025-02-18 DOI: 10.1016/j.rcim.2025.102990

Xiaoke Deng , Pengcheng Hu , Zhaoyu Li , Wenze Zhang , Dong He , Yuanzhi Chen

Five-axis continuous inspection is an innovative technology that allows for the efficient and precise inspection of freeform surfaces. Traditional methods for planning the five-axis inspection path rely on manually defined objective functions, which are heavily dependent on the expertise of professionals and often result in suboptimal paths. To overcome these challenges, we have developed a Reinforcement Learning (RL)-based approach for generating inspection paths. This method replaces the explicit objective function with an RL model that incorporates comprehensive geometric metrics of inspection surface, resulting in a high-performing head trajectory for the five-axis inspection path. Additionally, we have introduced a beam search-based method to generate a set of optimal head trajectories that cover the entire inspection surface. Our proposed method enables the automatic generation of short and smooth inspection paths without human intervention. Physical inspection experiments conducted on a five-axis inspection machine have demonstrated that our approach significantly improves inspection efficiency and automation compared to traditional benchmarks.

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引用次数: 0

Generalizing kinematic skill learning to energy efficient dynamic motion planning using optimized Dynamic Movement Primitives

IF 9.1 1区计算机科学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Robotics and Computer-integrated Manufacturing

Pub Date : 2025-02-18 DOI: 10.1016/j.rcim.2025.102983

Tian Xu , Siddharth Singh , Qing Chang

In manufacturing, automating the generation of dynamic trajectories for diverse robots and loads in response to kinematic task requirements presents a significant challenge. Previous research has primarily addressed kinematic trajectory generation and dynamic motion planning as separate endeavors, with integrated solutions rarely explored. This paper presents a novel methodology that combines reinforcement learning (RL)-based kinematic skill learning, dynamic modeling and an enhanced version of Dynamic Movement Primitives (DMP). Utilizing a pre-established skill library, the RL-enabled method generates multiple kinematic trajectories that fulfill the specific task requirements. These trajectories are further refined by dynamic modeling, selecting paths that minimize energy consumption tailored to specific robot types and loads. The newly proposed Optimized Normalized Dynamic Motion Primitive (ON-DMP) enhances obstacle avoidance with minimal energy consumption, remaining effective in novel environments. Validated through both simulated and real-world experiments, this methodology shows robust results in improving task completion in dynamic real-world environments without the need of reprogramming.

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引用次数: 0