Purpose This paper aims to provide a precise tracking control scheme for multi-input multi-output “MIMO” nonlinear systems with unknown input time-delay in industrial process. Design/methodology/approach The predictive control scheme based on multi-dimensional Taylor network (MTN) model is proposed. First, for the unknown input time-delay, the cross-correlation function is used to identify the input time-delay through just the input and output data. And then, the scheme of predictive control is designed based on the MTN model. It goes as follows: a recursive d-step-ahead MTN predictive model is developed to compensate the influence of time-delay, and the extended Kalman filter (EKF) algorithm is applied for its learning; the multistep predictive objective function is designed, and the optimal controlled output is determined by iterative refinement; and the convergence of MTN predictive model and the stability of closed-loop system are proved. Findings Simulation results show that the proposed scheme is of desirable generality and capable of performing the tracking control for MIMO nonlinear systems with unknown input time-delay in industrial process effectively, such as the continuous stirred tank reactor (CSTR) process, which provides a considerably improved performance and effectiveness. The proposed scheme promises strong robustness, low complexity and easy implementation. Research limitations/implications For the limitations of proposed scheme, the time-invariant time-delay is only considered in time-delay identification and control schemes. And the CSTR process is only introduced to prove that the proposed scheme can adapt to practical industrial scenario. Originality/value The originality of the paper is that the proposed MTN control scheme has good tracking performance, which solves the influence of time-delay, coupling and nonlinearity and the real-time performance for MIMO nonlinear systems with unknown input time-delay.
{"title":"MTN-based recursive d-step-ahead predictive control of MIMO nonlinear systems with unknown input time-delay in industrial process","authors":"Hong-sen Yan, Chenlong Li","doi":"10.1108/aa-08-2021-0102","DOIUrl":"https://doi.org/10.1108/aa-08-2021-0102","url":null,"abstract":"\u0000Purpose\u0000This paper aims to provide a precise tracking control scheme for multi-input multi-output “MIMO” nonlinear systems with unknown input time-delay in industrial process.\u0000\u0000\u0000Design/methodology/approach\u0000The predictive control scheme based on multi-dimensional Taylor network (MTN) model is proposed. First, for the unknown input time-delay, the cross-correlation function is used to identify the input time-delay through just the input and output data. And then, the scheme of predictive control is designed based on the MTN model. It goes as follows: a recursive d-step-ahead MTN predictive model is developed to compensate the influence of time-delay, and the extended Kalman filter (EKF) algorithm is applied for its learning; the multistep predictive objective function is designed, and the optimal controlled output is determined by iterative refinement; and the convergence of MTN predictive model and the stability of closed-loop system are proved.\u0000\u0000\u0000Findings\u0000Simulation results show that the proposed scheme is of desirable generality and capable of performing the tracking control for MIMO nonlinear systems with unknown input time-delay in industrial process effectively, such as the continuous stirred tank reactor (CSTR) process, which provides a considerably improved performance and effectiveness. The proposed scheme promises strong robustness, low complexity and easy implementation.\u0000\u0000\u0000Research limitations/implications\u0000For the limitations of proposed scheme, the time-invariant time-delay is only considered in time-delay identification and control schemes. And the CSTR process is only introduced to prove that the proposed scheme can adapt to practical industrial scenario.\u0000\u0000\u0000Originality/value\u0000The originality of the paper is that the proposed MTN control scheme has good tracking performance, which solves the influence of time-delay, coupling and nonlinearity and the real-time performance for MIMO nonlinear systems with unknown input time-delay.\u0000","PeriodicalId":55448,"journal":{"name":"Assembly Automation","volume":" ","pages":""},"PeriodicalIF":2.1,"publicationDate":"2022-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44291415","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Purpose The purpose of this study is developing the minimum parameter learning law for the weight updating, which reduces the updating of neural network (NN) weight only at triggering instants and makes a trade-off between the estimation accuracy and triggering frequency such that the computing complexity can be decreased. Besides that, a novel “soft” method is first constructed for the control updating at the triggered instants, to reduce the chattering effect of discontinued renewal of control. Addressing to the proposed control and updating method, a novel dead-zone condition with variable boundary about the triggered control signal is derived to ensure the positivity of adjacent execution intervals. Design/methodology/approach In this paper, to achieve the motion tracking of manipulator with uncertainty of system dynamics and the communication constraints in the control-execution channel, an adaptive event-triggered controller with NN identification is constructed to improve the transmission efficiency of control on the premise of the guaranteed performance. In the proposed method, the NN with intermittent updating is proposed to perform the uncertain approximation with the saved computation, and the triggered mechanism is constructed to regulate the transportation of the signal in the channel of controller-to-actuator. Findings According to the impulsive Lyapunov function, it can be proved that all the signals are semi-global uniformly ultimately bounded, and the positivity of adjacent execution intervals is also guaranteed by the proposed method. In addition, the chattering effect of control updating at the jumping instants can be relieved by the proposed “soft” mechanism, such that the control accuracy and stability can be guaranteed. Experiments on the JACO2 real manipulator are carried out to verify the effectiveness of the proposed scheme. Originality/value To the best of the author’s knowledge, this study is firstly to propose a “soft” method to reduce the chattering effect caused by discontinuous updating. Addressing to the updating method designed above, a novel dead-zone condition with variable threshold and boundary is first constructed to ensure the positivity of execution intervals.
{"title":"A novel event-triggered adaptive tracking control framework for a manipulator with aperiodic neural network estimation","authors":"Jie Gao","doi":"10.1108/aa-02-2022-0025","DOIUrl":"https://doi.org/10.1108/aa-02-2022-0025","url":null,"abstract":"\u0000Purpose\u0000The purpose of this study is developing the minimum parameter learning law for the weight updating, which reduces the updating of neural network (NN) weight only at triggering instants and makes a trade-off between the estimation accuracy and triggering frequency such that the computing complexity can be decreased. Besides that, a novel “soft” method is first constructed for the control updating at the triggered instants, to reduce the chattering effect of discontinued renewal of control. Addressing to the proposed control and updating method, a novel dead-zone condition with variable boundary about the triggered control signal is derived to ensure the positivity of adjacent execution intervals.\u0000\u0000\u0000Design/methodology/approach\u0000In this paper, to achieve the motion tracking of manipulator with uncertainty of system dynamics and the communication constraints in the control-execution channel, an adaptive event-triggered controller with NN identification is constructed to improve the transmission efficiency of control on the premise of the guaranteed performance. In the proposed method, the NN with intermittent updating is proposed to perform the uncertain approximation with the saved computation, and the triggered mechanism is constructed to regulate the transportation of the signal in the channel of controller-to-actuator.\u0000\u0000\u0000Findings\u0000According to the impulsive Lyapunov function, it can be proved that all the signals are semi-global uniformly ultimately bounded, and the positivity of adjacent execution intervals is also guaranteed by the proposed method. In addition, the chattering effect of control updating at the jumping instants can be relieved by the proposed “soft” mechanism, such that the control accuracy and stability can be guaranteed. Experiments on the JACO2 real manipulator are carried out to verify the effectiveness of the proposed scheme.\u0000\u0000\u0000Originality/value\u0000To the best of the author’s knowledge, this study is firstly to propose a “soft” method to reduce the chattering effect caused by discontinuous updating. Addressing to the updating method designed above, a novel dead-zone condition with variable threshold and boundary is first constructed to ensure the positivity of execution intervals.\u0000","PeriodicalId":55448,"journal":{"name":"Assembly Automation","volume":" ","pages":""},"PeriodicalIF":2.1,"publicationDate":"2022-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41826902","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Purpose This paper aims to study six degrees-of-freedom (6DOF) pose measurement of reflective metal casts by machine vision, analyze the problems existing in the positioning of metal casts by stereo vision sensor in unstructured environment and put forward the visual positioning and grasping strategy that can be used in industrial robot cell. Design/methodology/approach A multikeypoints detection network Binocular Attention Hourglass Net is constructed, which can complete the two-dimensional positioning of the left and right cameras of the stereo vision system at the same time and provide reconstruction information for three-dimensional pose measurement. Generate adversarial networks is introduced to enhance the image of local feature area of object surface, and the three-dimensional pose measurement of object is completed by combining RANSAC ellipse fitting algorithm and triangulation method. Findings The proposed method realizes the high-precision 6DOF positioning and grasping of reflective metal casts by industrial robots; it has been applied in many fields and solves the problem of difficult visual measurement of reflective casts. The experimental results show that the system exhibits superior recognition performance, which meets the requirements of the grasping task. Research limitations/implications Because of the chosen research approach, the research results may lack generalizability. The proposed method is more suitable for objects with plane positioning features. Originality/value This paper realizes the 6DOF pose measurement of reflective casts by vision system, and solves the problem of positioning and grasping such objects by industrial robot.
{"title":"A novel robotic 6DOF pose measurement strategy for large-size casts based on stereo vision","authors":"G. Wan, Fudong Li, Bingyou Liu, Shoujun Bai, Guofeng Wang, Kaisheng Xing","doi":"10.1108/aa-01-2022-0014","DOIUrl":"https://doi.org/10.1108/aa-01-2022-0014","url":null,"abstract":"\u0000Purpose\u0000This paper aims to study six degrees-of-freedom (6DOF) pose measurement of reflective metal casts by machine vision, analyze the problems existing in the positioning of metal casts by stereo vision sensor in unstructured environment and put forward the visual positioning and grasping strategy that can be used in industrial robot cell.\u0000\u0000\u0000Design/methodology/approach\u0000A multikeypoints detection network Binocular Attention Hourglass Net is constructed, which can complete the two-dimensional positioning of the left and right cameras of the stereo vision system at the same time and provide reconstruction information for three-dimensional pose measurement. Generate adversarial networks is introduced to enhance the image of local feature area of object surface, and the three-dimensional pose measurement of object is completed by combining RANSAC ellipse fitting algorithm and triangulation method.\u0000\u0000\u0000Findings\u0000The proposed method realizes the high-precision 6DOF positioning and grasping of reflective metal casts by industrial robots; it has been applied in many fields and solves the problem of difficult visual measurement of reflective casts. The experimental results show that the system exhibits superior recognition performance, which meets the requirements of the grasping task.\u0000\u0000\u0000Research limitations/implications\u0000Because of the chosen research approach, the research results may lack generalizability. The proposed method is more suitable for objects with plane positioning features.\u0000\u0000\u0000Originality/value\u0000This paper realizes the 6DOF pose measurement of reflective casts by vision system, and solves the problem of positioning and grasping such objects by industrial robot.\u0000","PeriodicalId":55448,"journal":{"name":"Assembly Automation","volume":" ","pages":""},"PeriodicalIF":2.1,"publicationDate":"2022-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42134552","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Purpose This paper aims to study a parameter tuning method for the active disturbance rejection control (ADRC) to improve the anti-interference ability and position tracking of the performance of the servo system, and to ensure the stability and accuracy of practical applications. Design/methodology/approach This study proposes a parameter self-tuning method for ADRC based on an improved glowworm swarm optimization algorithm. The algorithm is improved by using sine and cosine local optimization operators and an adaptive mutation strategy. The improved algorithm is then used for parameter tuning of the ADRC to improve the anti-interference ability of the control system and ensure the accuracy of the controller parameters. Findings The authors designed an optimization model based on MATLAB, selected examples of simulation and experimental research and compared it with the standard glowworm swarm optimization algorithm, particle swarm algorithm and artificial bee colony algorithm. The results show that the response time of using the improved glowworm swarm optimization algorithm to optimize the auto-disturbance rejection control is short; there is no overshoot; the tracking process is relatively stable; the anti-interference ability is strong; and the optimization effect is better. Originality/value The innovation of this study is to improve the glowworm swarm optimization algorithm, propose a sine and cosine, local optimization operator, expand the firefly search space and introduce a new adaptive mutation strategy to adaptively adjust the mutation probability based on the fitness value, improve the global search ability of the algorithm and use the improved algorithm to adjust the parameters of the active disturbance rejection controller.
{"title":"Parameter tuning of auto disturbance rejection controller based on improved glowworm swarm optimization algorithm","authors":"Bing-Tuan Gao, W. Shen, Ye Dai, Yongtai Ye","doi":"10.1108/aa-12-2021-0188","DOIUrl":"https://doi.org/10.1108/aa-12-2021-0188","url":null,"abstract":"\u0000Purpose\u0000This paper aims to study a parameter tuning method for the active disturbance rejection control (ADRC) to improve the anti-interference ability and position tracking of the performance of the servo system, and to ensure the stability and accuracy of practical applications.\u0000\u0000\u0000Design/methodology/approach\u0000This study proposes a parameter self-tuning method for ADRC based on an improved glowworm swarm optimization algorithm. The algorithm is improved by using sine and cosine local optimization operators and an adaptive mutation strategy. The improved algorithm is then used for parameter tuning of the ADRC to improve the anti-interference ability of the control system and ensure the accuracy of the controller parameters.\u0000\u0000\u0000Findings\u0000The authors designed an optimization model based on MATLAB, selected examples of simulation and experimental research and compared it with the standard glowworm swarm optimization algorithm, particle swarm algorithm and artificial bee colony algorithm. The results show that the response time of using the improved glowworm swarm optimization algorithm to optimize the auto-disturbance rejection control is short; there is no overshoot; the tracking process is relatively stable; the anti-interference ability is strong; and the optimization effect is better.\u0000\u0000\u0000Originality/value\u0000The innovation of this study is to improve the glowworm swarm optimization algorithm, propose a sine and cosine, local optimization operator, expand the firefly search space and introduce a new adaptive mutation strategy to adaptively adjust the mutation probability based on the fitness value, improve the global search ability of the algorithm and use the improved algorithm to adjust the parameters of the active disturbance rejection controller.\u0000","PeriodicalId":55448,"journal":{"name":"Assembly Automation","volume":" ","pages":""},"PeriodicalIF":2.1,"publicationDate":"2022-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43198819","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Zhonglai Tian, Hongtai Cheng, Z. Du, Zongbei Jiang, Yeping Wang
Purpose The purpose of this paper is to estimate the contact-consistent object poses during contact-rich manipulation tasks based only on visual sensors. Design/methodology/approach The method follows a four-step procedure. Initially, the raw object poses are retrieved using the available object pose estimation method and filtered using Kalman filter with nominal model; second, a group of particles are randomly generated for each pose and evaluated the corresponding object contact state using the contact simulation software. A probability guided particle averaging method is proposed to balance the accuracy and safety issues; third, the independently estimated contact states are fused in a hidden Markov model to remove the abnormal contact state observations; finally, the object poses are refined by averaging the contact state consistent particles. Findings The experiments are performed to evaluate the effectiveness of the proposed methods. The results show that the method can achieve smooth and accurate pose estimation results and the estimated contact states are consistent with ground truth. Originality/value This paper proposes a method to obtain contact-consistent poses and contact states of objects using only visual sensors. The method tries to recover the true contact state from inaccurate visual information by fusing contact simulations results and contact consistency assumptions. The method can be used to extract pose and contact information from object manipulation tasks by just observing the demonstration, which can provide a new way for the robot to learn complex manipulation tasks.
{"title":"Contact-consistent visual object pose estimation for contact-rich robotic manipulation tasks","authors":"Zhonglai Tian, Hongtai Cheng, Z. Du, Zongbei Jiang, Yeping Wang","doi":"10.1108/aa-10-2021-0128","DOIUrl":"https://doi.org/10.1108/aa-10-2021-0128","url":null,"abstract":"\u0000Purpose\u0000The purpose of this paper is to estimate the contact-consistent object poses during contact-rich manipulation tasks based only on visual sensors.\u0000\u0000\u0000Design/methodology/approach\u0000The method follows a four-step procedure. Initially, the raw object poses are retrieved using the available object pose estimation method and filtered using Kalman filter with nominal model; second, a group of particles are randomly generated for each pose and evaluated the corresponding object contact state using the contact simulation software. A probability guided particle averaging method is proposed to balance the accuracy and safety issues; third, the independently estimated contact states are fused in a hidden Markov model to remove the abnormal contact state observations; finally, the object poses are refined by averaging the contact state consistent particles.\u0000\u0000\u0000Findings\u0000The experiments are performed to evaluate the effectiveness of the proposed methods. The results show that the method can achieve smooth and accurate pose estimation results and the estimated contact states are consistent with ground truth.\u0000\u0000\u0000Originality/value\u0000This paper proposes a method to obtain contact-consistent poses and contact states of objects using only visual sensors. The method tries to recover the true contact state from inaccurate visual information by fusing contact simulations results and contact consistency assumptions. The method can be used to extract pose and contact information from object manipulation tasks by just observing the demonstration, which can provide a new way for the robot to learn complex manipulation tasks.\u0000","PeriodicalId":55448,"journal":{"name":"Assembly Automation","volume":" ","pages":""},"PeriodicalIF":2.1,"publicationDate":"2022-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46904857","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Qiang Zhang, Zijian Ye, Siyu Shao, Tianlin Niu, Yuwei Zhao
Purpose The current studies on remaining useful life (RUL) prediction mainly rely on convolutional neural networks (CNNs) and long short-term memories (LSTMs) and do not take full advantage of the attention mechanism, resulting in lack of prediction accuracy. To further improve the performance of the above models, this study aims to propose a novel end-to-end RUL prediction framework, called convolutional recurrent attention network (CRAN) to achieve high accuracy. Design/methodology/approach The proposed CRAN is a CNN-LSTM-based model that effectively combines the powerful feature extraction ability of CNN and sequential processing capability of LSTM. The channel attention mechanism, spatial attention mechanism and LSTM attention mechanism are incorporated in CRAN, assigning different attention coefficients to CNN and LSTM. First, features of the bearing vibration data are extracted from both time and frequency domain. Next, the training and testing set are constructed. Then, the CRAN is trained offline using the training set. Finally, online RUL estimation is performed by applying data from the testing set to the trained CRAN. Findings CNN-LSTM-based models have higher RUL prediction accuracy than CNN-based and LSTM-based models. Using a combination of max pooling and average pooling can reduce the loss of feature information, and in addition, the structure of the serial attention mechanism is superior to the parallel attention structure. Comparing the proposed CRAN with six different state-of-the-art methods, for the predicted results of two testing bearings, the proposed CRAN has an average reduction in the root mean square error of 57.07/80.25%, an average reduction in the mean absolute error of 62.27/85.87% and an average improvement in score of 12.65/6.57%. Originality/value This article provides a novel end-to-end rolling bearing RUL prediction framework, which can provide a reference for the formulation of bearing maintenance programs in the industry.
{"title":"Remaining useful life prediction of rolling bearings based on convolutional recurrent attention network","authors":"Qiang Zhang, Zijian Ye, Siyu Shao, Tianlin Niu, Yuwei Zhao","doi":"10.1108/aa-08-2021-0113","DOIUrl":"https://doi.org/10.1108/aa-08-2021-0113","url":null,"abstract":"\u0000Purpose\u0000The current studies on remaining useful life (RUL) prediction mainly rely on convolutional neural networks (CNNs) and long short-term memories (LSTMs) and do not take full advantage of the attention mechanism, resulting in lack of prediction accuracy. To further improve the performance of the above models, this study aims to propose a novel end-to-end RUL prediction framework, called convolutional recurrent attention network (CRAN) to achieve high accuracy.\u0000\u0000\u0000Design/methodology/approach\u0000The proposed CRAN is a CNN-LSTM-based model that effectively combines the powerful feature extraction ability of CNN and sequential processing capability of LSTM. The channel attention mechanism, spatial attention mechanism and LSTM attention mechanism are incorporated in CRAN, assigning different attention coefficients to CNN and LSTM. First, features of the bearing vibration data are extracted from both time and frequency domain. Next, the training and testing set are constructed. Then, the CRAN is trained offline using the training set. Finally, online RUL estimation is performed by applying data from the testing set to the trained CRAN.\u0000\u0000\u0000Findings\u0000CNN-LSTM-based models have higher RUL prediction accuracy than CNN-based and LSTM-based models. Using a combination of max pooling and average pooling can reduce the loss of feature information, and in addition, the structure of the serial attention mechanism is superior to the parallel attention structure. Comparing the proposed CRAN with six different state-of-the-art methods, for the predicted results of two testing bearings, the proposed CRAN has an average reduction in the root mean square error of 57.07/80.25%, an average reduction in the mean absolute error of 62.27/85.87% and an average improvement in score of 12.65/6.57%.\u0000\u0000\u0000Originality/value\u0000This article provides a novel end-to-end rolling bearing RUL prediction framework, which can provide a reference for the formulation of bearing maintenance programs in the industry.\u0000","PeriodicalId":55448,"journal":{"name":"Assembly Automation","volume":" ","pages":""},"PeriodicalIF":2.1,"publicationDate":"2022-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42351687","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Hang Su, Wen Qi, Y. Schmirander, S. E. Ovur, Shuting Cai, Xiaoming Xiong
Purpose The purpose of this paper is to develop a human activity-aware adaptive shared control solution for human–robot interaction in surgical operation. Hands-on control and teleoperation are two main procedures switched frequently in teleoperated minimally invasive surgery (MIS). The detailed human activity in the procedures can be defined and recognized using the sensor information. In this paper, a novel continuous adaptive shared control method is proposed for manipulators with Cartesian impedance control in the surgical scenario. Design/methodology/approach A human activity-aware shared control solution by adjusting the weight function is introduced to achieve smooth transition among different human activities, including hands-on control and teleoperation. Instead of introducing various controllers and switching among them during the surgical procedures, the proposed solution integrated all the human activity-based controllers into a single controller and the transition among the procedures is smooth and stable. The effectiveness of the proposed control approach was verified in a lab setup environment. The results prove that the robot behavior is stable and smooth. The algorithm is feasible and can achieve a human activity-aware adaptive shared control solution for human–robot interaction in surgical operation. Findings Based on the experiment, the results confirm that the proposed human activity-aware adaptive shared control solution can switch the device behavior automatically using the real-time sensor information. The transition between different activities is smooth and stable. Practical implications For teleoperated surgical applications, the proposed method integrated different controllers for various human activities into a single controller by recognizing the activities using the real-time sensor information and the transition between different procedures is smooth and stable. It eases the surgical work for the surgeon and enhances the safety during the transition of control modes. The presented scheme provides a general solution to address the switching of working procedures in teleoperated MIS. Originality/value To the best of the authors’ knowledge, this paper is the first to propose human activity-aware adaptive shared control solution for human–robot interaction in surgical operations.
{"title":"A human activity-aware shared control solution for medical human–robot interaction","authors":"Hang Su, Wen Qi, Y. Schmirander, S. E. Ovur, Shuting Cai, Xiaoming Xiong","doi":"10.1108/aa-12-2021-0174","DOIUrl":"https://doi.org/10.1108/aa-12-2021-0174","url":null,"abstract":"\u0000Purpose\u0000The purpose of this paper is to develop a human activity-aware adaptive shared control solution for human–robot interaction in surgical operation. Hands-on control and teleoperation are two main procedures switched frequently in teleoperated minimally invasive surgery (MIS). The detailed human activity in the procedures can be defined and recognized using the sensor information. In this paper, a novel continuous adaptive shared control method is proposed for manipulators with Cartesian impedance control in the surgical scenario.\u0000\u0000\u0000Design/methodology/approach\u0000A human activity-aware shared control solution by adjusting the weight function is introduced to achieve smooth transition among different human activities, including hands-on control and teleoperation. Instead of introducing various controllers and switching among them during the surgical procedures, the proposed solution integrated all the human activity-based controllers into a single controller and the transition among the procedures is smooth and stable. The effectiveness of the proposed control approach was verified in a lab setup environment. The results prove that the robot behavior is stable and smooth. The algorithm is feasible and can achieve a human activity-aware adaptive shared control solution for human–robot interaction in surgical operation.\u0000\u0000\u0000Findings\u0000Based on the experiment, the results confirm that the proposed human activity-aware adaptive shared control solution can switch the device behavior automatically using the real-time sensor information. The transition between different activities is smooth and stable.\u0000\u0000\u0000Practical implications\u0000For teleoperated surgical applications, the proposed method integrated different controllers for various human activities into a single controller by recognizing the activities using the real-time sensor information and the transition between different procedures is smooth and stable. It eases the surgical work for the surgeon and enhances the safety during the transition of control modes. The presented scheme provides a general solution to address the switching of working procedures in teleoperated MIS.\u0000\u0000\u0000Originality/value\u0000To the best of the authors’ knowledge, this paper is the first to propose human activity-aware adaptive shared control solution for human–robot interaction in surgical operations.\u0000","PeriodicalId":55448,"journal":{"name":"Assembly Automation","volume":" ","pages":""},"PeriodicalIF":2.1,"publicationDate":"2022-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48905714","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Purpose This paper aims to propose an optimization method to automatically adjust the spatial route of multibend pipes to meet the assembly demands in constrained space. Design/methodology/approach The compact geometric parameters that uniquely determine the pipe route are analyzed. Besides, the relationship between these parameters and the end pose is revealed based on the exponential product formula. Mathematical representations for the engineering constraints, including the end pose restriction, collision interference, manufacture ability and geometric limitations, are further established. On this basis, the adjustment of the spatial route is formulated as a multiconstraint optimization problem. A modified particle swarm optimization method based on the combination of gradient projection and swarm intelligence is designed to find the near-optimal pipe that meets the required assembly demands. Findings The experimental results show that the proposed method can effectively find the feasible pipe route that satisfies the engineering constraints and the end pose requirement is highly guaranteed. Originality/value The proposed method can automate the geometric adjustment of multi-bend pipes to meet the actual assembly demands, which significantly reduces manual efforts and guarantees high accuracy. The results demonstrate the possibility of further applications in the pipe assembly or design process, especially in ships, aerospace products or pressure vessels.
{"title":"Optimization method for spatial route adjustment of multi-bends pipes considering assembly demands","authors":"Kunyong Chen, Yong Zhao, Yuming Liu, Haidong Yu, Shunzhou Huang","doi":"10.1108/aa-10-2021-0132","DOIUrl":"https://doi.org/10.1108/aa-10-2021-0132","url":null,"abstract":"\u0000Purpose\u0000This paper aims to propose an optimization method to automatically adjust the spatial route of multibend pipes to meet the assembly demands in constrained space.\u0000\u0000\u0000Design/methodology/approach\u0000The compact geometric parameters that uniquely determine the pipe route are analyzed. Besides, the relationship between these parameters and the end pose is revealed based on the exponential product formula. Mathematical representations for the engineering constraints, including the end pose restriction, collision interference, manufacture ability and geometric limitations, are further established. On this basis, the adjustment of the spatial route is formulated as a multiconstraint optimization problem. A modified particle swarm optimization method based on the combination of gradient projection and swarm intelligence is designed to find the near-optimal pipe that meets the required assembly demands.\u0000\u0000\u0000Findings\u0000The experimental results show that the proposed method can effectively find the feasible pipe route that satisfies the engineering constraints and the end pose requirement is highly guaranteed.\u0000\u0000\u0000Originality/value\u0000The proposed method can automate the geometric adjustment of multi-bend pipes to meet the actual assembly demands, which significantly reduces manual efforts and guarantees high accuracy. The results demonstrate the possibility of further applications in the pipe assembly or design process, especially in ships, aerospace products or pressure vessels.\u0000","PeriodicalId":55448,"journal":{"name":"Assembly Automation","volume":" ","pages":""},"PeriodicalIF":2.1,"publicationDate":"2022-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45992486","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Purpose The purpose of this paper is to design a smart handheld device with force regulating function, which demonstrates the concept of patient-specialized tools. Design/methodology/approach This handheld device integrates an electrical bioimpedance (EBI) sensor for tissue measurement and a constant force regulation mechanism for ensuring stable tool–tissue contact. Particular focuses in this study are on the design of the constant force regulation mechanism whose design process is through genetic algorithm optimization and finite element simulation. In addition, the output force can be changed to the desired value by adjusting the cross-sectional area of the generated spring. Findings The following two specific applications based on ex vivo tissues are used for evaluating the designed device. One is in terms of safety of interaction with delicate tissue while the other is for compensating involuntary tissue motion. The results of both examples show that the handheld device is able to provide an output force with a small standard deviation. Originality/value In this paper, a handheld device with force regulation mechanism is designed for specific patients based on the genetic algorithm optimization and finite element simulation. The device can maintain a steady and safe interaction force during the EBI measurement on fragile tissues or moving tissues, to improve the sensing accuracy and to avoid tissue damage. Such functions of the proposed device are evaluated through a series of experiments and the device is demonstrated to be effective.
{"title":"Smart handheld medical device with patient-specific force regulation mechanism","authors":"Zhuoqi Cheng, Jiale He, Pengjie Lin, Min He, Jing Guo, Xinwei Chen, Shuting Cai, Xiaoming Xiong","doi":"10.1108/aa-10-2021-0126","DOIUrl":"https://doi.org/10.1108/aa-10-2021-0126","url":null,"abstract":"\u0000Purpose\u0000The purpose of this paper is to design a smart handheld device with force regulating function, which demonstrates the concept of patient-specialized tools.\u0000\u0000\u0000Design/methodology/approach\u0000This handheld device integrates an electrical bioimpedance (EBI) sensor for tissue measurement and a constant force regulation mechanism for ensuring stable tool–tissue contact. Particular focuses in this study are on the design of the constant force regulation mechanism whose design process is through genetic algorithm optimization and finite element simulation. In addition, the output force can be changed to the desired value by adjusting the cross-sectional area of the generated spring.\u0000\u0000\u0000Findings\u0000The following two specific applications based on ex vivo tissues are used for evaluating the designed device. One is in terms of safety of interaction with delicate tissue while the other is for compensating involuntary tissue motion. The results of both examples show that the handheld device is able to provide an output force with a small standard deviation.\u0000\u0000\u0000Originality/value\u0000In this paper, a handheld device with force regulation mechanism is designed for specific patients based on the genetic algorithm optimization and finite element simulation. The device can maintain a steady and safe interaction force during the EBI measurement on fragile tissues or moving tissues, to improve the sensing accuracy and to avoid tissue damage. Such functions of the proposed device are evaluated through a series of experiments and the device is demonstrated to be effective.\u0000","PeriodicalId":55448,"journal":{"name":"Assembly Automation","volume":" ","pages":""},"PeriodicalIF":2.1,"publicationDate":"2022-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44955972","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Junshan Hu, Xinyue Sun, W. Tian, Shanyong Xuan, Yang Yan, Wang Changrui, W. Liao
Purpose Aerospace assembly demands high drilling position accuracy for fastener holes. Hole position error correction is a key issue to meet the required hole position accuracy. This paper aims to propose a combined hole position error correction method to achieve high positioning accuracy. Design/methodology/approach The bilinear interpolation surface function based on the shape of the aerospace structure is capable of dealing with position error of non-gravity deformation. A gravity deformation model is developed based on mechanics theory to efficiently correct deformation error caused by gravity. Moreover, three solution strategies of the average, least-squares and genetic optimization algorithms are used to solve the coefficients in the gravity deformation model to further improve position accuracy and efficiency. Findings Experimental validation shows that the combined position error correction method proposed in this paper significantly reduces the position errors of fastener holes from 1.106 to 0.123 mm. The total position error is reduced by 43.49% compared with the traditional mechanics theory method. Research limitations/implications The position error correlation method could reach an accuracy of millimeter or submillimeter scale, which may not satisfy higher precision. Practical implications The proposed position error correction method has been integrated into the automatic drilling machine to ensure the drilling position accuracy. Social implications The proposed position error method could promote the wide application of automatic drilling and riveting machining system in aerospace industry. Originality/value A combined position error correction method and the complete roadmap for error compensation are proposed. The position accuracy of fastener holes is reduced stably below 0.2 mm, which can fulfill the requirements of aero-structural assembly.
{"title":"A combined hole position error correction method for automated drilling of large-span aerospace assembly structures","authors":"Junshan Hu, Xinyue Sun, W. Tian, Shanyong Xuan, Yang Yan, Wang Changrui, W. Liao","doi":"10.1108/aa-05-2021-0053","DOIUrl":"https://doi.org/10.1108/aa-05-2021-0053","url":null,"abstract":"\u0000Purpose\u0000Aerospace assembly demands high drilling position accuracy for fastener holes. Hole position error correction is a key issue to meet the required hole position accuracy. This paper aims to propose a combined hole position error correction method to achieve high positioning accuracy.\u0000\u0000\u0000Design/methodology/approach\u0000The bilinear interpolation surface function based on the shape of the aerospace structure is capable of dealing with position error of non-gravity deformation. A gravity deformation model is developed based on mechanics theory to efficiently correct deformation error caused by gravity. Moreover, three solution strategies of the average, least-squares and genetic optimization algorithms are used to solve the coefficients in the gravity deformation model to further improve position accuracy and efficiency.\u0000\u0000\u0000Findings\u0000Experimental validation shows that the combined position error correction method proposed in this paper significantly reduces the position errors of fastener holes from 1.106 to 0.123 mm. The total position error is reduced by 43.49% compared with the traditional mechanics theory method.\u0000\u0000\u0000Research limitations/implications\u0000The position error correlation method could reach an accuracy of millimeter or submillimeter scale, which may not satisfy higher precision.\u0000\u0000\u0000Practical implications\u0000The proposed position error correction method has been integrated into the automatic drilling machine to ensure the drilling position accuracy.\u0000\u0000\u0000Social implications\u0000The proposed position error method could promote the wide application of automatic drilling and riveting machining system in aerospace industry.\u0000\u0000\u0000Originality/value\u0000A combined position error correction method and the complete roadmap for error compensation are proposed. The position accuracy of fastener holes is reduced stably below 0.2 mm, which can fulfill the requirements of aero-structural assembly.\u0000","PeriodicalId":55448,"journal":{"name":"Assembly Automation","volume":" ","pages":""},"PeriodicalIF":2.1,"publicationDate":"2022-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47509728","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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