Purpose When the mobile manipulator is traveling on an unconstructed terrain, the external disturbance is generated. The load on the end of the mobile manipulator will be affected strictly by the disturbance. The purpose of this paper is to reject the disturbance and keep the end effector in a stable pose all the time, a control method is proposed for the onboard manipulator. Design/methodology/approach In this paper, the kinematics and dynamics models of the end pose stability control system for the tracked robot are built. Through the guidance of this model information, the control framework based on active disturbance rejection control (ADRC) is designed, which keeps the attitude of the end of the manipulator stable in the pitch, roll and yaw direction. Meanwhile, the control algorithm is operated with cloud computing because the research object, the rescue robot, aims to be lightweight and execute work with remote manipulation. Findings The challenging simulation experiments demonstrate that the methodology can achieve valid stability control performance in the challenging terrain road in terms of robustness and real-time. Originality/value This research facilitates the stable posture control of the end-effector of the mobile manipulator and maintains it in a suitable stable operating environment. The entire system can normally work even in dynamic disturbance scenarios and uncertain nonlinear modeling. Furthermore, an example is given to guide the parameter tuning of ADRC by using model information and estimate the unknown internal modeling uncertainty, which is difficult to be modeled or identified.
{"title":"Stability control for end effect of mobile manipulator in uneven terrain based on active disturbance rejection control","authors":"Chuang Cheng, Hui Zhang, Hui Peng, Zhiqian Zhou, Bailiang Chen, Zeng Zhiwen, Huimin Lu","doi":"10.1108/AA-10-2020-0157","DOIUrl":"https://doi.org/10.1108/AA-10-2020-0157","url":null,"abstract":"\u0000Purpose\u0000When the mobile manipulator is traveling on an unconstructed terrain, the external disturbance is generated. The load on the end of the mobile manipulator will be affected strictly by the disturbance. The purpose of this paper is to reject the disturbance and keep the end effector in a stable pose all the time, a control method is proposed for the onboard manipulator.\u0000\u0000\u0000Design/methodology/approach\u0000In this paper, the kinematics and dynamics models of the end pose stability control system for the tracked robot are built. Through the guidance of this model information, the control framework based on active disturbance rejection control (ADRC) is designed, which keeps the attitude of the end of the manipulator stable in the pitch, roll and yaw direction. Meanwhile, the control algorithm is operated with cloud computing because the research object, the rescue robot, aims to be lightweight and execute work with remote manipulation.\u0000\u0000\u0000Findings\u0000The challenging simulation experiments demonstrate that the methodology can achieve valid stability control performance in the challenging terrain road in terms of robustness and real-time.\u0000\u0000\u0000Originality/value\u0000This research facilitates the stable posture control of the end-effector of the mobile manipulator and maintains it in a suitable stable operating environment. The entire system can normally work even in dynamic disturbance scenarios and uncertain nonlinear modeling. Furthermore, an example is given to guide the parameter tuning of ADRC by using model information and estimate the unknown internal modeling uncertainty, which is difficult to be modeled or identified.\u0000","PeriodicalId":55448,"journal":{"name":"Assembly Automation","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2021-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48808164","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}
Guojun Zhang, Feng Ni, Liu Hong, Jiang Zainan, Guocai Yang, Li Chongyang
The purpose of this paper is to transfer the impedance regulation of manual belt grinding to robot belt grinding control.,This paper presents a novel methodology for transmitting human impedance regulation skills to robot control in robot belt grinding. First, according to the human grinding experimental data, the skilled worker’s arm impedance regulation is calculated. Next, the human skills are encapsulated as the statistical learning model where the kernel parameters are learned from the demonstration data by Gaussian process regression (GPR) algorithms. The desired profiles of robot are generated by the task planner based on the learned skill knowledge model. Lastly, the learned skill knowledge model is integrated with an adaptive hybrid position-force controller over the trajectory and force of end-effector in robot belt grinding task.,Manual grinding skills are represented and transferred to robot belt grinding for higher grinding quality of the workpiece.,The impedance of the manual grinding is estimated by k-means++ algorithm at different grinding phases. Manual grinding skills (e.g. trajectory, impedance regulation) are represented and modeled by GMM and GPR algorithms. The desired trajectory, force and impedance of robot are generated by the planner based on the learned skills knowledge model. An adaptive hybrid position-force controller is designed based on learned skill knowledge model. This paper proposes a torque-tracking controller to suppress the vibration in robot belt grinding process.
{"title":"Learning impedance regulation skills for robot belt grinding from human demonstrations","authors":"Guojun Zhang, Feng Ni, Liu Hong, Jiang Zainan, Guocai Yang, Li Chongyang","doi":"10.1108/AA-08-2020-0110","DOIUrl":"https://doi.org/10.1108/AA-08-2020-0110","url":null,"abstract":"The purpose of this paper is to transfer the impedance regulation of manual belt grinding to robot belt grinding control.,This paper presents a novel methodology for transmitting human impedance regulation skills to robot control in robot belt grinding. First, according to the human grinding experimental data, the skilled worker’s arm impedance regulation is calculated. Next, the human skills are encapsulated as the statistical learning model where the kernel parameters are learned from the demonstration data by Gaussian process regression (GPR) algorithms. The desired profiles of robot are generated by the task planner based on the learned skill knowledge model. Lastly, the learned skill knowledge model is integrated with an adaptive hybrid position-force controller over the trajectory and force of end-effector in robot belt grinding task.,Manual grinding skills are represented and transferred to robot belt grinding for higher grinding quality of the workpiece.,The impedance of the manual grinding is estimated by k-means++ algorithm at different grinding phases. Manual grinding skills (e.g. trajectory, impedance regulation) are represented and modeled by GMM and GPR algorithms. The desired trajectory, force and impedance of robot are generated by the planner based on the learned skills knowledge model. An adaptive hybrid position-force controller is designed based on learned skill knowledge model. This paper proposes a torque-tracking controller to suppress the vibration in robot belt grinding process.","PeriodicalId":55448,"journal":{"name":"Assembly Automation","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2021-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42089067","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 provide a knowledge-enabled digital twin for smart design (KDT-SD) of aircraft assembly line (AAL) to enhance the AAL efficiency, performance and visibility. Modern AALs usually need to have capabilities such as digital-physical interaction and self-evaluation that brings significant challenges to traditional design method for AAL. The digital twin (DT) combining with reusable knowledge, as the key technologies in this framework, is introduced to promote the design process by configuring, understanding and evaluating design scheme. Design/methodology/approach The proposed KDT-SD framework is designed with the introduction of DT and knowledge. First, dynamic design knowledge library (DDK-Lib) is established which could support the various activities of DT in the entire design process. Then, the knowledge-driven digital AAL modeling method is proposed. At last, knowledge-based smart evaluation is used to understand and identify the design flaws, which could further improvement of the design scheme. Findings By means of the KDT-SD framework proposed, it is possible to apply DT to reduce the complexity and discover design flaws in AAL design. Moreover, the knowledge equips DT with the capacities of rapid modeling and smart evaluation that improve design efficiency and quality. Originality/value The proposed KDT-SD framework can provide efficient design of AAL and evaluate the design performance in advance so that the feasibility of design scheme can be improved as much as possible.
{"title":"Knowledge-enabled digital twin for smart designing of aircraft assembly line","authors":"Xiao Chang, Xiaoliang Jia, Kuo Liu, Hao Hu","doi":"10.1108/AA-09-2020-0133","DOIUrl":"https://doi.org/10.1108/AA-09-2020-0133","url":null,"abstract":"\u0000Purpose\u0000The purpose of this paper is to provide a knowledge-enabled digital twin for smart design (KDT-SD) of aircraft assembly line (AAL) to enhance the AAL efficiency, performance and visibility. Modern AALs usually need to have capabilities such as digital-physical interaction and self-evaluation that brings significant challenges to traditional design method for AAL. The digital twin (DT) combining with reusable knowledge, as the key technologies in this framework, is introduced to promote the design process by configuring, understanding and evaluating design scheme.\u0000\u0000\u0000Design/methodology/approach\u0000The proposed KDT-SD framework is designed with the introduction of DT and knowledge. First, dynamic design knowledge library (DDK-Lib) is established which could support the various activities of DT in the entire design process. Then, the knowledge-driven digital AAL modeling method is proposed. At last, knowledge-based smart evaluation is used to understand and identify the design flaws, which could further improvement of the design scheme.\u0000\u0000\u0000Findings\u0000By means of the KDT-SD framework proposed, it is possible to apply DT to reduce the complexity and discover design flaws in AAL design. Moreover, the knowledge equips DT with the capacities of rapid modeling and smart evaluation that improve design efficiency and quality.\u0000\u0000\u0000Originality/value\u0000The proposed KDT-SD framework can provide efficient design of AAL and evaluate the design performance in advance so that the feasibility of design scheme can be improved as much as possible.\u0000","PeriodicalId":55448,"journal":{"name":"Assembly Automation","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2021-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45263768","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}
Fashu Xu, Rui Huang, Hong Cheng, Mingyuan Fan, Jing Qiu
Purpose This paper aims at the problem of attaching the data of doctors, patients and the real-time sensor data of the exoskeleton to the cloud in intelligent rehabilitation applications. This study designed the exoskeleton cloud-brain platform and validated its safety assessment. Design/methodology/approach According to the dimension of data and the transmission speed, this paper implements a three-layer cloud-brain platform of exoskeleton based on Alibaba Cloud's Lambda-like architecture. At the same time, given the human–machine safety status detection problem of the exoskeleton, this paper built a personalized machine-learning safety detection module for users with the multi-dimensional sensor data cloned by the cloud-brain platform. This module includes an abnormality detection model, prediction model and state classification model of the human–machine state. Findings These functions of the exoskeleton cloud-brain and the algorithms based on it were validated by the experiments, they meet the needs of use. Originality/value This thesis innovatively proposes a cloud-brain platform for exoskeletons, beginning the digitalization and intelligence of the exoskeletal rehabilitation process and laying the foundation for future intelligent assistance systems.
{"title":"Exoskeleton cloud-brain platform and its application in safety assessment","authors":"Fashu Xu, Rui Huang, Hong Cheng, Mingyuan Fan, Jing Qiu","doi":"10.1108/AA-11-2020-0184","DOIUrl":"https://doi.org/10.1108/AA-11-2020-0184","url":null,"abstract":"\u0000Purpose\u0000This paper aims at the problem of attaching the data of doctors, patients and the real-time sensor data of the exoskeleton to the cloud in intelligent rehabilitation applications. This study designed the exoskeleton cloud-brain platform and validated its safety assessment.\u0000\u0000\u0000Design/methodology/approach\u0000According to the dimension of data and the transmission speed, this paper implements a three-layer cloud-brain platform of exoskeleton based on Alibaba Cloud's Lambda-like architecture. At the same time, given the human–machine safety status detection problem of the exoskeleton, this paper built a personalized machine-learning safety detection module for users with the multi-dimensional sensor data cloned by the cloud-brain platform. This module includes an abnormality detection model, prediction model and state classification model of the human–machine state.\u0000\u0000\u0000Findings\u0000These functions of the exoskeleton cloud-brain and the algorithms based on it were validated by the experiments, they meet the needs of use.\u0000\u0000\u0000Originality/value\u0000This thesis innovatively proposes a cloud-brain platform for exoskeletons, beginning the digitalization and intelligence of the exoskeletal rehabilitation process and laying the foundation for future intelligent assistance systems.\u0000","PeriodicalId":55448,"journal":{"name":"Assembly Automation","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2021-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41481397","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}
Wang Zhengtuo, Xu Yuetong, Guanhua Xu, Fu Jianzhong, Yu Jiongyan, Gu Tianyi
Purpose In this work, the authors aim to provide a set of convenient methods for generating training data, and then develop a deep learning method based on point clouds to estimate the pose of target for robot grasping. Design/methodology/approach This work presents a deep learning method PointSimGrasp on point clouds for robot grasping. In PointSimGrasp, a point cloud emulator is introduced to generate training data and a pose estimation algorithm, which, based on deep learning, is designed. After trained with the emulation data set, the pose estimation algorithm could estimate the pose of target. Findings In experiment part, an experimental platform is built, which contains a six-axis industrial robot, a binocular structured-light sensor and a base platform with adjustable inclination. A data set that contains three subsets is set up on the experimental platform. After trained with the emulation data set, the PointSimGrasp is tested on the experimental data set, and an average translation error of about 2–3 mm and an average rotation error of about 2–5 degrees are obtained. Originality/value The contributions are as follows: first, a deep learning method on point clouds is proposed to estimate 6D pose of target; second, a convenient training method for pose estimation algorithm is presented and a point cloud emulator is introduced to generate training data; finally, an experimental platform is built, and the PointSimGrasp is tested on the platform.
{"title":"Simulation and deep learning on point clouds for robot grasping","authors":"Wang Zhengtuo, Xu Yuetong, Guanhua Xu, Fu Jianzhong, Yu Jiongyan, Gu Tianyi","doi":"10.1108/AA-07-2020-0096","DOIUrl":"https://doi.org/10.1108/AA-07-2020-0096","url":null,"abstract":"\u0000Purpose\u0000In this work, the authors aim to provide a set of convenient methods for generating training data, and then develop a deep learning method based on point clouds to estimate the pose of target for robot grasping.\u0000\u0000\u0000Design/methodology/approach\u0000This work presents a deep learning method PointSimGrasp on point clouds for robot grasping. In PointSimGrasp, a point cloud emulator is introduced to generate training data and a pose estimation algorithm, which, based on deep learning, is designed. After trained with the emulation data set, the pose estimation algorithm could estimate the pose of target.\u0000\u0000\u0000Findings\u0000In experiment part, an experimental platform is built, which contains a six-axis industrial robot, a binocular structured-light sensor and a base platform with adjustable inclination. A data set that contains three subsets is set up on the experimental platform. After trained with the emulation data set, the PointSimGrasp is tested on the experimental data set, and an average translation error of about 2–3 mm and an average rotation error of about 2–5 degrees are obtained.\u0000\u0000\u0000Originality/value\u0000The contributions are as follows: first, a deep learning method on point clouds is proposed to estimate 6D pose of target; second, a convenient training method for pose estimation algorithm is presented and a point cloud emulator is introduced to generate training data; finally, an experimental platform is built, and the PointSimGrasp is tested on the platform.\u0000","PeriodicalId":55448,"journal":{"name":"Assembly Automation","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2021-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45207359","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 provide a new hydrostatic actuator controlled by a piezoelectric piston pump and to reveal its characteristics. Design/methodology/approach In this paper, a piezoelectric pump with passive poppet valves and hydraulic displacement amplifier is designed as a new control component in a hydrostatic actuator for high actuation capacity. A component-level mathematical model is established to describe the system characteristics. Simulation verification for cases under typical conditions is implemented to evaluate the delivery behavior of the pump and the carrying ability of the actuator. Findings By using the displacement amplifier and the passive distributing valves, simulation demonstrates that the pump can deliver flow rate up to 3 L/min, and the actuator controlled by this pump can push an object weighing approximately 50 kg. In addition, it is particularly important to decide a proper amplification ratio of the amplifier in the pump for better actuation performance. Originality/value The piezoelectric pump presented in this paper has its potential to light hydrostatic actuator. The model constructed in this paper is valid for characteristic analysis and performance evaluation of this pump and actuators.
{"title":"Simulation on an electro-hydrostatic actuator controlled by a high-pressure piezoelectric pump with a displacement amplifier","authors":"Bin Wang, Nanyue Xu, Pengyuan Wu, Rongfei Yang","doi":"10.1108/AA-04-2020-0054","DOIUrl":"https://doi.org/10.1108/AA-04-2020-0054","url":null,"abstract":"\u0000Purpose\u0000The purpose of this paper is to provide a new hydrostatic actuator controlled by a piezoelectric piston pump and to reveal its characteristics.\u0000\u0000\u0000Design/methodology/approach\u0000In this paper, a piezoelectric pump with passive poppet valves and hydraulic displacement amplifier is designed as a new control component in a hydrostatic actuator for high actuation capacity. A component-level mathematical model is established to describe the system characteristics. Simulation verification for cases under typical conditions is implemented to evaluate the delivery behavior of the pump and the carrying ability of the actuator.\u0000\u0000\u0000Findings\u0000By using the displacement amplifier and the passive distributing valves, simulation demonstrates that the pump can deliver flow rate up to 3 L/min, and the actuator controlled by this pump can push an object weighing approximately 50 kg. In addition, it is particularly important to decide a proper amplification ratio of the amplifier in the pump for better actuation performance.\u0000\u0000\u0000Originality/value\u0000The piezoelectric pump presented in this paper has its potential to light hydrostatic actuator. The model constructed in this paper is valid for characteristic analysis and performance evaluation of this pump and actuators.\u0000","PeriodicalId":55448,"journal":{"name":"Assembly Automation","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2021-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48133262","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 Indoor localization is a key tool for robot navigation in indoor environments. Traditionally, robot navigation depends on one sensor to perform autonomous localization. This paper aims to enhance the navigation performance of mobile robots, a multiple data fusion (MDF) method is proposed for indoor environments. Design/methodology/approach Here, multiple sensor data i.e. collected information of inertial measurement unit, odometer and laser radar, are used. Then, an extended Kalman filter (EKF) is used to incorporate these multiple data and the mobile robot can perform autonomous localization according to the proposed EKF-based MDF method in complex indoor environments. Findings The proposed method has experimentally been verified in the different indoor environments, i.e. office, passageway and exhibition hall. Experimental results show that the EKF-based MDF method can achieve the best localization performance and robustness in the process of navigation. Originality/value Indoor localization precision is mostly related to the collected data from multiple sensors. The proposed method can incorporate these collected data reasonably and can guide the mobile robot to perform autonomous navigation (AN) in indoor environments. Therefore, the output of this paper would be used for AN in complex and unknown indoor environments.
{"title":"An EKF-based multiple data fusion for mobile robot indoor localization","authors":"Guangbing Zhou, Jing Luo, Shugong Xu, Shunqing Zhang, Shige Meng, Kui Xiang","doi":"10.1108/AA-12-2020-0199","DOIUrl":"https://doi.org/10.1108/AA-12-2020-0199","url":null,"abstract":"\u0000Purpose\u0000Indoor localization is a key tool for robot navigation in indoor environments. Traditionally, robot navigation depends on one sensor to perform autonomous localization. This paper aims to enhance the navigation performance of mobile robots, a multiple data fusion (MDF) method is proposed for indoor environments.\u0000\u0000\u0000Design/methodology/approach\u0000Here, multiple sensor data i.e. collected information of inertial measurement unit, odometer and laser radar, are used. Then, an extended Kalman filter (EKF) is used to incorporate these multiple data and the mobile robot can perform autonomous localization according to the proposed EKF-based MDF method in complex indoor environments.\u0000\u0000\u0000Findings\u0000The proposed method has experimentally been verified in the different indoor environments, i.e. office, passageway and exhibition hall. Experimental results show that the EKF-based MDF method can achieve the best localization performance and robustness in the process of navigation.\u0000\u0000\u0000Originality/value\u0000Indoor localization precision is mostly related to the collected data from multiple sensors. The proposed method can incorporate these collected data reasonably and can guide the mobile robot to perform autonomous navigation (AN) in indoor environments. Therefore, the output of this paper would be used for AN in complex and unknown indoor environments.\u0000","PeriodicalId":55448,"journal":{"name":"Assembly Automation","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2021-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41906165","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 achieve stable grasping and dexterous in-hand manipulation, the control of the multi-fingered robotic hand is a difficult problem as the hand has many degrees of freedom with various grasp configurations. Design/methodology/approach To achieve this goal, a novel object-level impedance control framework with optimized grasp force and grasp quality is proposed for multi-fingered robotic hand grasping and in-hand manipulation. The minimal grasp force optimization aims to achieve stable grasping satisfying friction cone constraint while keeping appropriate contact forces without damage to the object. With the optimized grasp quality function, optimal grasp quality can be obtained by dynamically sliding on the object from initial grasp configuration to final grasp configuration. By the proposed controller, the in-hand manipulation of the grasped object can be achieved with compliance to the environment force. The control performance of the closed-loop robotic system is guaranteed by appropriately choosing the design parameters as proved by a Lyapunove function. Findings Simulations are conducted to validate the efficiency and performance of the proposed controller with a three-fingered robotic hand. Originality/value This paper presents a method for robotic optimal grasping and in-hand manipulation with a compliant controller. It may inspire other related researchers and has great potential for practical usage in a widespread of robot applications.
{"title":"Optimal grasp force for robotic grasping and in-hand manipulation with impedance control","authors":"Xiaoqing Li, Ziyu Chen, Chao Ma","doi":"10.1108/AA-11-2020-0180","DOIUrl":"https://doi.org/10.1108/AA-11-2020-0180","url":null,"abstract":"\u0000Purpose\u0000The purpose of this paper is to achieve stable grasping and dexterous in-hand manipulation, the control of the multi-fingered robotic hand is a difficult problem as the hand has many degrees of freedom with various grasp configurations.\u0000\u0000\u0000Design/methodology/approach\u0000To achieve this goal, a novel object-level impedance control framework with optimized grasp force and grasp quality is proposed for multi-fingered robotic hand grasping and in-hand manipulation. The minimal grasp force optimization aims to achieve stable grasping satisfying friction cone constraint while keeping appropriate contact forces without damage to the object. With the optimized grasp quality function, optimal grasp quality can be obtained by dynamically sliding on the object from initial grasp configuration to final grasp configuration. By the proposed controller, the in-hand manipulation of the grasped object can be achieved with compliance to the environment force. The control performance of the closed-loop robotic system is guaranteed by appropriately choosing the design parameters as proved by a Lyapunove function.\u0000\u0000\u0000Findings\u0000Simulations are conducted to validate the efficiency and performance of the proposed controller with a three-fingered robotic hand.\u0000\u0000\u0000Originality/value\u0000This paper presents a method for robotic optimal grasping and in-hand manipulation with a compliant controller. It may inspire other related researchers and has great potential for practical usage in a widespread of robot applications.\u0000","PeriodicalId":55448,"journal":{"name":"Assembly Automation","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2021-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47611084","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 unfold the role that job rotation plays in a lean cell. Unlike many studies, the authors consider heterogeneous operators with dynamic performance factor that is impacted by the assignment and scheduling decisions. The purpose is to derive an understanding of the underlying effects of job rotations on performance metrics in a lean cell. The authors use an optimization framework and an experimental design methodology for sensitivity analysis of the input parameters. Design/methodology/approach The approach is an integration of three stages. The authors propose a set-based optimization model that considers human behavior parameters. They also solve the problem with two meta-heuristic algorithms and an efficient local search algorithm. Further, the authors run a post-optimality analysis by conducting a design of experiments using the response surface methodology (RSM). Findings The results of the optimization model reveal that the job rotation schedules and the human cognitive metrics influence the performance of the lean cell. The results of the sensitivity analysis further show that the objective function and the job rotation frequencies are highly sensitive to the other input parameters. Based on the findings from the RSM, the authors derive general rules for the job rotations in a lean cell given the ranges in other input variables. Originality/value The authors integrate the job rotation scheduling model with human behavioral and cognitive parameters and formulate the problem in a lean cell for the first time in the literature. In addition, they use the RSM for the first time in this context and offer a post-optimality analysis that reveals important information about the impact of the job rotations on the performance of operators and the entire working cell.
{"title":"The job rotation scheduling problem considering human cognitive effects: an integrated approach","authors":"A. Ayough, Farbod Farhadi, M. Zandieh","doi":"10.1108/AA-05-2020-0061","DOIUrl":"https://doi.org/10.1108/AA-05-2020-0061","url":null,"abstract":"\u0000Purpose\u0000This paper aims to unfold the role that job rotation plays in a lean cell. Unlike many studies, the authors consider heterogeneous operators with dynamic performance factor that is impacted by the assignment and scheduling decisions. The purpose is to derive an understanding of the underlying effects of job rotations on performance metrics in a lean cell. The authors use an optimization framework and an experimental design methodology for sensitivity analysis of the input parameters.\u0000\u0000\u0000Design/methodology/approach\u0000The approach is an integration of three stages. The authors propose a set-based optimization model that considers human behavior parameters. They also solve the problem with two meta-heuristic algorithms and an efficient local search algorithm. Further, the authors run a post-optimality analysis by conducting a design of experiments using the response surface methodology (RSM).\u0000\u0000\u0000Findings\u0000The results of the optimization model reveal that the job rotation schedules and the human cognitive metrics influence the performance of the lean cell. The results of the sensitivity analysis further show that the objective function and the job rotation frequencies are highly sensitive to the other input parameters. Based on the findings from the RSM, the authors derive general rules for the job rotations in a lean cell given the ranges in other input variables.\u0000\u0000\u0000Originality/value\u0000The authors integrate the job rotation scheduling model with human behavioral and cognitive parameters and formulate the problem in a lean cell for the first time in the literature. In addition, they use the RSM for the first time in this context and offer a post-optimality analysis that reveals important information about the impact of the job rotations on the performance of operators and the entire working cell.\u0000","PeriodicalId":55448,"journal":{"name":"Assembly Automation","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2021-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41419914","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：