Some dynamic factors, such as inertial forces and friction, may affect therobot trajectory accuracy. But these effects are not taken into account in robot motion controlschemes. Dynamic control methods, on the other h...Some dynamic factors, such as inertial forces and friction, may affect therobot trajectory accuracy. But these effects are not taken into account in robot motion controlschemes. Dynamic control methods, on the other hand, require the dynamic model of robot and theimplementation of new type controller. A method to improve robot trajectory accuracy by dynamiccompensation in robot motion control system is proposed. The dynamic compensation is applied as anadditional velocity feedforward and a multilayer neural network is employed to realize the robotinverse dynamics. The complicated dynamic parameter identification problem becomes a learningprocess of neural network connecting weights under supervision. The finite Fourier series is used toactivate each actuator of robot joints for obtaining training samples. Robot control system,consisting of an industrial computer and a digital motion controller, is implemented. The system isof open architecture with velocity feedforward function. The proposed method is not model-based andcombines the advantages of close-loop position control and computed torque control. Experimentalresults have shown that the method is validatities to improve the robot trajectory accuracy.展开更多
In applications such as marine rescue,marine science,archaeology,and offshore industries,autonomous underwater vehicles(AUVs)are frequently used for survey missions and monitoring tasks,with most operations being perf...In applications such as marine rescue,marine science,archaeology,and offshore industries,autonomous underwater vehicles(AUVs)are frequently used for survey missions and monitoring tasks,with most operations being performed by manned submersibles or remotely operated vehicles(ROVs)equipped with robotic arms,as they can be operated remotely for days without problems.However,they require expensive marine vessels and specialist pilots to operate them.Scientists exploring oceans are no longer satisfied with the use of manned submersibles and ROVs.There is a growing desire for seabed exploration to be performed using smarter,more flexible,and automated equipment.By improving the field operation and intervention capability of AUVs,large-scale and long-range seafloor exploration and sampling can be performed without the support of a mother ship,making it a more effective,economical,convenient,and rapid means of seafloor exploration and sampling operations,and playing a critical role in marine resource exploration.In this study,we explored the integration technology of underwater electric robotic arms and AUVs and designed a new set of electric manipulators suitable for water depths greater than 500 m.The reliability of the key components was analyzed by finite element analysis and,based on the theory of robot kinematics and dynamics,simulations were performed to verify the reliability of the key components.Experiments were conducted on land and underwater,trajectory tracking experiments were completed,and the experimental data in air and water were compared and analyzed.Finally,the objectives for further research on the autonomous control of the manipulator underwater were proposed.展开更多
In order to improve the trajectory tracking precision and reduce the synchronization error of a 6-DOF lightweight robot, nonlinear proportion-deviation （N-PD） cross-coupling synchronization control strategy based on...In order to improve the trajectory tracking precision and reduce the synchronization error of a 6-DOF lightweight robot, nonlinear proportion-deviation （N-PD） cross-coupling synchronization control strategy based on adjacent coupling error analysis is presented. The mathematical models of the robot, including kinematic model, dynamic model and spline trajectory planing, are established and verified. Since it is difficult to describe the real-time contour error of the robot for complex trajectory, the adjacent coupling error is analyzed to solve the problem. Combined with nonlinear control and coupling performance of the robot, N-PD cross-coupling synchronization controller is designed and validated by simulation analysis. A servo control experimental system which mainly consists of laser tracking system, the robot mechanical system and EtherCAT based servo control system is constructed. The synchronization error is significantly decreased and the maximum trajectory error is reduced from 0.33 mm to 0.1 mm. The effectiveness of the control algorithm is validated by the experimental results, thus the control strategy can improve the robot＇s trajectory tracking precision significantly.展开更多
基金This project is supported by National 863 Project of China(No.9802-01).
文摘Some dynamic factors, such as inertial forces and friction, may affect therobot trajectory accuracy. But these effects are not taken into account in robot motion controlschemes. Dynamic control methods, on the other hand, require the dynamic model of robot and theimplementation of new type controller. A method to improve robot trajectory accuracy by dynamiccompensation in robot motion control system is proposed. The dynamic compensation is applied as anadditional velocity feedforward and a multilayer neural network is employed to realize the robotinverse dynamics. The complicated dynamic parameter identification problem becomes a learningprocess of neural network connecting weights under supervision. The finite Fourier series is used toactivate each actuator of robot joints for obtaining training samples. Robot control system,consisting of an industrial computer and a digital motion controller, is implemented. The system isof open architecture with velocity feedforward function. The proposed method is not model-based andcombines the advantages of close-loop position control and computed torque control. Experimentalresults have shown that the method is validatities to improve the robot trajectory accuracy.
基金This work is supported by the Key Research and Development Program of Zhejiang Province(No.2021C03013),China.
文摘In applications such as marine rescue,marine science,archaeology,and offshore industries,autonomous underwater vehicles(AUVs)are frequently used for survey missions and monitoring tasks,with most operations being performed by manned submersibles or remotely operated vehicles(ROVs)equipped with robotic arms,as they can be operated remotely for days without problems.However,they require expensive marine vessels and specialist pilots to operate them.Scientists exploring oceans are no longer satisfied with the use of manned submersibles and ROVs.There is a growing desire for seabed exploration to be performed using smarter,more flexible,and automated equipment.By improving the field operation and intervention capability of AUVs,large-scale and long-range seafloor exploration and sampling can be performed without the support of a mother ship,making it a more effective,economical,convenient,and rapid means of seafloor exploration and sampling operations,and playing a critical role in marine resource exploration.In this study,we explored the integration technology of underwater electric robotic arms and AUVs and designed a new set of electric manipulators suitable for water depths greater than 500 m.The reliability of the key components was analyzed by finite element analysis and,based on the theory of robot kinematics and dynamics,simulations were performed to verify the reliability of the key components.Experiments were conducted on land and underwater,trajectory tracking experiments were completed,and the experimental data in air and water were compared and analyzed.Finally,the objectives for further research on the autonomous control of the manipulator underwater were proposed.
基金Project(2015AA043003)supported by National High-technology Research and Development Program of ChinaProject(GY2016ZB0068)supported by Application Technology Research and Development Program of Heilongjiang Province,ChinaProject(SKLR201301A03)supported by Self-planned Task of State Key Laboratory of Robotics and System(Harbin Institute of Technology),China
文摘In order to improve the trajectory tracking precision and reduce the synchronization error of a 6-DOF lightweight robot, nonlinear proportion-deviation （N-PD） cross-coupling synchronization control strategy based on adjacent coupling error analysis is presented. The mathematical models of the robot, including kinematic model, dynamic model and spline trajectory planing, are established and verified. Since it is difficult to describe the real-time contour error of the robot for complex trajectory, the adjacent coupling error is analyzed to solve the problem. Combined with nonlinear control and coupling performance of the robot, N-PD cross-coupling synchronization controller is designed and validated by simulation analysis. A servo control experimental system which mainly consists of laser tracking system, the robot mechanical system and EtherCAT based servo control system is constructed. The synchronization error is significantly decreased and the maximum trajectory error is reduced from 0.33 mm to 0.1 mm. The effectiveness of the control algorithm is validated by the experimental results, thus the control strategy can improve the robot＇s trajectory tracking precision significantly.
