Revealing the relations among robotic comprehensive performance,configuration,scales and working tasks is the basis to optimize robotic mechanism. Due to the correlation and diversity of the single performance indexes...Revealing the relations among robotic comprehensive performance,configuration,scales and working tasks is the basis to optimize robotic mechanism. Due to the correlation and diversity of the single performance indexes,statistical principles of linear dimension reduction and nonlinear dimension reduction are introduced into comprehensive performance analysis and evaluation for typical serial robot. The robotic mechanism's configuration,scales and task with the best comprehensive performance can be obtained by principal component analysis( PCA) and kernel principal component analysis( KPCA) respectively. The results show that KPCA can reveal the nonlinear relations among different single performance indexes more effectively and provide more comprehensive performance information than PCA. Thus,task-oriented method of serial robot for mechanism analysis and evaluation is proposed,which also provides scientific research basis for the mechanism synthesis and optimum task order.展开更多
Industrial serial robots need high stiffness to keep absolute pose accuracy and meet the requirements in practical applications. However, the weak stiffness feature of robot joints and the payloads affected on robot e...Industrial serial robots need high stiffness to keep absolute pose accuracy and meet the requirements in practical applications. However, the weak stiffness feature of robot joints and the payloads affected on robot end-effector, which will also increase the pose error of robot. Especially, the existing calibration methods often consider under no-payload condition without discussing the payload state. In this paper, we report a new industrial serial robot composed by a new harmonic reducer: Model-Y, based on high accuracy and high stiffness, and a kinematic parameter calibration algorithm which is based on a harmonic reducer forcedeformation model. To decrease the accuracy effects of payload, an iterative calibration method for kinematic parameters with payload situation was proposed. Simulation and experiments are conducted to verify the effectiveness of the proposed calibration method using the self-developed industrial serial robot. The results show a remarkably improved accuracy in absolute position and orientation with the robot's payload range. The position mean error has 70% decreased to 0.1 mm and the orientation mean error diminished to less than 0.01° after calibration with compensation. Additionally, online linear and circular tests are carried out to evaluate the position error of the robot during large-scale spatial and low-speed continuous movement. The accuracy is consistent with the previous calibration results, indicating the effectiveness and advantages of the proposed strategy in this article.展开更多
A new solution to the inverse position analysis of the redundant serial robot is presented.The inverse position analysis problem of the redundant serial robot is transformed into a minimization problem and then the op...A new solution to the inverse position analysis of the redundant serial robot is presented.The inverse position analysis problem of the redundant serial robot is transformed into a minimization problem and then the optimization method is adopted to solve the nonlinear least square problem with the analytic form of a new Jacobi matrix.In this way,the inverse solution of the redundant serial robot can be searched out quickly under the desired precision when the positions of the three non-collinear end effector points are given.The inverse position analysis of the 7R redundant serial robot is illustrated as an example and the simulation results verify the efficiency of the proposed algorithm.展开更多
基金Sponsored by the National Natural Science Foundation of China(Grant No.51075005)the Beijing City Science and Technology Project(Grant No.Z131100005313009)
文摘Revealing the relations among robotic comprehensive performance,configuration,scales and working tasks is the basis to optimize robotic mechanism. Due to the correlation and diversity of the single performance indexes,statistical principles of linear dimension reduction and nonlinear dimension reduction are introduced into comprehensive performance analysis and evaluation for typical serial robot. The robotic mechanism's configuration,scales and task with the best comprehensive performance can be obtained by principal component analysis( PCA) and kernel principal component analysis( KPCA) respectively. The results show that KPCA can reveal the nonlinear relations among different single performance indexes more effectively and provide more comprehensive performance information than PCA. Thus,task-oriented method of serial robot for mechanism analysis and evaluation is proposed,which also provides scientific research basis for the mechanism synthesis and optimum task order.
基金supported by the National Key Research and Development Program for Robotics Serialized Harmonic Reducer Fatigue Performance Analysis and Prediction and Life Enhancement Technology Research(Grant No. 2017YFB1300603)。
文摘Industrial serial robots need high stiffness to keep absolute pose accuracy and meet the requirements in practical applications. However, the weak stiffness feature of robot joints and the payloads affected on robot end-effector, which will also increase the pose error of robot. Especially, the existing calibration methods often consider under no-payload condition without discussing the payload state. In this paper, we report a new industrial serial robot composed by a new harmonic reducer: Model-Y, based on high accuracy and high stiffness, and a kinematic parameter calibration algorithm which is based on a harmonic reducer forcedeformation model. To decrease the accuracy effects of payload, an iterative calibration method for kinematic parameters with payload situation was proposed. Simulation and experiments are conducted to verify the effectiveness of the proposed calibration method using the self-developed industrial serial robot. The results show a remarkably improved accuracy in absolute position and orientation with the robot's payload range. The position mean error has 70% decreased to 0.1 mm and the orientation mean error diminished to less than 0.01° after calibration with compensation. Additionally, online linear and circular tests are carried out to evaluate the position error of the robot during large-scale spatial and low-speed continuous movement. The accuracy is consistent with the previous calibration results, indicating the effectiveness and advantages of the proposed strategy in this article.
基金the National Natural Science Foundation of China (No.50905102)the China Postdoctoral Science Foundation (No.200801199)the Natural Science Foundation of Guangdong Province (Nos.8351503101000001 and 10151503101000033)
文摘A new solution to the inverse position analysis of the redundant serial robot is presented.The inverse position analysis problem of the redundant serial robot is transformed into a minimization problem and then the optimization method is adopted to solve the nonlinear least square problem with the analytic form of a new Jacobi matrix.In this way,the inverse solution of the redundant serial robot can be searched out quickly under the desired precision when the positions of the three non-collinear end effector points are given.The inverse position analysis of the 7R redundant serial robot is illustrated as an example and the simulation results verify the efficiency of the proposed algorithm.
