It is crucial for implementing force/position control of robotic manipulator under the constraint of unknown environment to determine the force control and the position control directions. This paper presents an on l...It is crucial for implementing force/position control of robotic manipulator under the constraint of unknown environment to determine the force control and the position control directions. This paper presents an on line algorithm to real timely estimate the tangent and the normal vectors of the constraint surface based on the measured contact force under the consideration of frictional force. A fuzzy synthesis policy is proposed to coordinate the conflict between the compliant force control and the stiff position control. An experimental study on an AdeptThree, a SCARA type robotic manipulator, is conducted. The experimental results show that the policy presented in the paper is effective.展开更多
A force control strategy for position controlled robotic manipulators is presented. On line force feedback data are employed to estimate the local shape of the unknown constraint. The estimated vectors are used to ge...A force control strategy for position controlled robotic manipulators is presented. On line force feedback data are employed to estimate the local shape of the unknown constraint. The estimated vectors are used to generate the virtual reference trajectory for the target impedance model that is driven by the force error to produce command position. By following the command position trajectory the robotic manipulator can follow the unknown constraint surface while keeping an acceptable force error in a manner depicted by the target impedance model. Computer simulation on a 3 linked planar manipulator and experimental studies on an Adept 3, an SCARA type robotic manipulator, are conducted to verify the force tracking capability of the proposed control strategy.展开更多
A decentralized adaptive neural network sliding mode position/force control scheme is proposed for constrained reconfigurable manipulators. Different from the decentralized control strategy in multi-manipulator cooper...A decentralized adaptive neural network sliding mode position/force control scheme is proposed for constrained reconfigurable manipulators. Different from the decentralized control strategy in multi-manipulator cooperation, the proposed decentralized position/force control scheme can be applied to series constrained reconfigurable manipulators. By multiplying each row of Jacobian matrix in the dynamics by contact force vector, the converted joint torque is obtained. Furthermore, using desired information of other joints instead of their actual values, the dynamics can be represented as a set of interconnected subsystems by model decomposition technique. An adaptive neural network controller is introduced to approximate the unknown dynamics of subsystem. The interconnection and the whole error term are removed by employing an adaptive sliding mode term. And then, the Lyapunov stability theory guarantees the stability of the closed-loop system. Finally, two reconfigurable manipulators with different configurations are employed to show the effectiveness of the proposed decentralized position/force control scheme.展开更多
A position/force hybrid control system based on impedance control scheme is designed to align a small gripper to a special ring object. The vision information provided by microscope vision system is used as the feedba...A position/force hybrid control system based on impedance control scheme is designed to align a small gripper to a special ring object. The vision information provided by microscope vision system is used as the feedback to indicate the position relationship between the gripper and the ring object. Multiple image features of the gripper and the ring object are extracted to estimate the relative positions between them. The end-effector of the gripper is tracked using the extracted features to keep the gripper moving in the field of view. The force information from the force sensor serves as the feedback to ensure that the contact force between the gripper and the ring object is limited in a small safe range. Experimental results verify the effectiveness of the proposed control strategy.展开更多
A neural network control scheme with mixed H2/H∞performance was proposed for robot force/position control under parameter uncertainties and external disturbances. The mixed H2/H∞tracking performance ensures both rob...A neural network control scheme with mixed H2/H∞performance was proposed for robot force/position control under parameter uncertainties and external disturbances. The mixed H2/H∞tracking performance ensures both robust stability under a prescribed attenuation level for external disturbance and H2optimal tracking. The neural network was introduced to adaptively estimate nonlinear uncertainties, improving the system’s performance under parameter uncertainties as well as obtaining the H2/H∞tracking performance. The simulation shows that the control method performs better even when the system is under large modeling uncertainties and external disturbances.展开更多
This paper proposes a feasible force/position control method for industrial robots utilized for such tasks as grinding, polishing, deburring, and so on. Specifically, an adaptive force/position control strategy is des...This paper proposes a feasible force/position control method for industrial robots utilized for such tasks as grinding, polishing, deburring, and so on. Specifically, an adaptive force/position control strategy is designed in this paper which regulates the contact force between a robot and a workpiece to reach any given set-point exponentially fast, and enables the robot to follow a chosen trajectory simultaneously without requiring prior knowledge of the system parameters. The stability of the closed-loop system is analyzed by Lyapunov techniques. To test the validity of the force/position control method, some simulation results are first collected for the closed-loop system. Furthermore, some experiments are implemented on a 5DOF （degree of freedom） industrial robot for the constructed adaptive force controller. Both simulation and experiment results demonstrate the superior performance of the designed adaptive force/position control strategy.展开更多
A hybrid position/force controller is designed for the joint 2 and the joint 3 of thePUMA 560 robot.The hybrid controller includes a multilayered neural network,which canidentify the dynamics of the contacted environm...A hybrid position/force controller is designed for the joint 2 and the joint 3 of thePUMA 560 robot.The hybrid controller includes a multilayered neural network,which canidentify the dynamics of the contacted environment and can optimize the parameters of PIDcontroller.The experimental results show that after having been trained,the robot has sta-ble response to the training patterns and strong adaptive ability to the situation between thepatterns.展开更多
A simple robust scheme of parallel force/position control is proposed in this paper to deal with two problems for non-planar constraint surface and nonlinear mechanical feature of environment： i） uncertainties in en...A simple robust scheme of parallel force/position control is proposed in this paper to deal with two problems for non-planar constraint surface and nonlinear mechanical feature of environment： i） uncertainties in environment that are usually not available or difficult to be determined in most practical situations; ii） stability problem or/and integrator windup due to the integration of force error in the force dominance rule in parallel force/position control. It shows that this robust scheme is a good alternative for anti-windup. In the presence of environment uncertainties, global asymptotic stability of the resulting closed-loop system is guaranteed; it environment with complex characteristics. Finally, numerical robot manipulator. also shows robustness of the proposed controller to uncertain simulation verifies results via contact task of a two rigid-links展开更多
Collision avoidance is always difficult in the planning path for a mobile robot. In this paper, the virtual force field between a mobile robot and an obstacle is formed and regulated to maintain a desired distance by ...Collision avoidance is always difficult in the planning path for a mobile robot. In this paper, the virtual force field between a mobile robot and an obstacle is formed and regulated to maintain a desired distance by hybrid force control algorithm. Since uncertainties from robot dynamics and obstacle degrade the performance of a collision avoidance task, intelligent control is used to compensate for the uncertainties. A radial basis function （RBF） neural network is used to regulate the force field of an accurate distance between a robot and an obstacle in this paper and then simulation studies are conducted to confirm that the proposed algorithm is effective.展开更多
Force control based on neural networks is presented. Under the framework of hybrid control, an RBF neural network is used to compensate for all the uncertainties from robot dynamics and unknown environment first. The ...Force control based on neural networks is presented. Under the framework of hybrid control, an RBF neural network is used to compensate for all the uncertainties from robot dynamics and unknown environment first. The technique will improve the adaptability to environment stiffness when the end-effector is in contact with the environment, and does not require any a priori knowledge on the upper bound of syste uncertainties. Moreover, it need not compute the inverse of inertia matrix. Learning algorithms for neural networks to minimize the force error directly are designed. Simulation results have shown a better force/position tracking when neural network is used.展开更多
Antarctic scientific expedition has important strategic significance. It is an inevitable trend to apply robots to assist researchers during the Antarctic expedition. However, the robot manipula- tors at present have ...Antarctic scientific expedition has important strategic significance. It is an inevitable trend to apply robots to assist researchers during the Antarctic expedition. However, the robot manipula- tors at present have a series of problems and unable to meet the requirements of the Antarctic expe- dition. In this paper, a novel Antarctic modular robot manipulator is proposed, which has a compact structure with modular joints. The robot manipulator has high reliability, and quick assembling-and- disassembling ability. Through well wires arranging and thermal controlling, the manipulator can better adapt to the Antarctic environment. In addition, the work space of the manipulator is serious- ly analyzed, and a new hybrid position/force control method is adopted to make the manipulator per- form better. Simulation results validate the control method and show that the robot manipulator has a good performance to meet the requirements of Antarctic expedition.展开更多
In order to overcome the shortcomings of the traditional sling suspension method,such as complex structure of suspension truss,large running resistance,and low precision of position servo system,a gravity compensation...In order to overcome the shortcomings of the traditional sling suspension method,such as complex structure of suspension truss,large running resistance,and low precision of position servo system,a gravity compensation method of lunar rover based on the combination of active suspension and active position following of magnetic levitation is proposed,and the overall design is carried out.The dynamic model of the suspension module of microgravity compensation system was established,and the decoupling control between the constant force component and the position servo component was analyzed and verified.The constant tension control was achieved by using hybrid force/position control.The position following control was realized by using fuzzy adaptive PID(proportional⁃integral⁃differential)control.The stable suspension control was realized based on the principle of force balance.The simulation results show that the compensation accuracy of constant tension could reach more than 95%,the position deviation was less than 5 mm,the position deviation angle was less than 0.025°,and the air gap recovered stability within 0.1 s.The gravity compensation system has excellent dynamic performance and can meet the requirements of microgravity simulation experiment of lunar rover.展开更多
文摘It is crucial for implementing force/position control of robotic manipulator under the constraint of unknown environment to determine the force control and the position control directions. This paper presents an on line algorithm to real timely estimate the tangent and the normal vectors of the constraint surface based on the measured contact force under the consideration of frictional force. A fuzzy synthesis policy is proposed to coordinate the conflict between the compliant force control and the stiff position control. An experimental study on an AdeptThree, a SCARA type robotic manipulator, is conducted. The experimental results show that the policy presented in the paper is effective.
文摘A force control strategy for position controlled robotic manipulators is presented. On line force feedback data are employed to estimate the local shape of the unknown constraint. The estimated vectors are used to generate the virtual reference trajectory for the target impedance model that is driven by the force error to produce command position. By following the command position trajectory the robotic manipulator can follow the unknown constraint surface while keeping an acceptable force error in a manner depicted by the target impedance model. Computer simulation on a 3 linked planar manipulator and experimental studies on an Adept 3, an SCARA type robotic manipulator, are conducted to verify the force tracking capability of the proposed control strategy.
基金Project(61374051,61603387)supported by the National Natural Science Foundation of ChinaProjects(20150520112JH,20160414033GH)supported by the Scientific and Technological Development Plan in Jilin Province of ChinaProject(20150102)supported by Opening Funding of State Key Laboratory of Management and Control for Complex Systems,China
文摘A decentralized adaptive neural network sliding mode position/force control scheme is proposed for constrained reconfigurable manipulators. Different from the decentralized control strategy in multi-manipulator cooperation, the proposed decentralized position/force control scheme can be applied to series constrained reconfigurable manipulators. By multiplying each row of Jacobian matrix in the dynamics by contact force vector, the converted joint torque is obtained. Furthermore, using desired information of other joints instead of their actual values, the dynamics can be represented as a set of interconnected subsystems by model decomposition technique. An adaptive neural network controller is introduced to approximate the unknown dynamics of subsystem. The interconnection and the whole error term are removed by employing an adaptive sliding mode term. And then, the Lyapunov stability theory guarantees the stability of the closed-loop system. Finally, two reconfigurable manipulators with different configurations are employed to show the effectiveness of the proposed decentralized position/force control scheme.
基金supported by National Natural Science Foundation of China(No.61105036 and 61227804)
文摘A position/force hybrid control system based on impedance control scheme is designed to align a small gripper to a special ring object. The vision information provided by microscope vision system is used as the feedback to indicate the position relationship between the gripper and the ring object. Multiple image features of the gripper and the ring object are extracted to estimate the relative positions between them. The end-effector of the gripper is tracked using the extracted features to keep the gripper moving in the field of view. The force information from the force sensor serves as the feedback to ensure that the contact force between the gripper and the ring object is limited in a small safe range. Experimental results verify the effectiveness of the proposed control strategy.
文摘A neural network control scheme with mixed H2/H∞performance was proposed for robot force/position control under parameter uncertainties and external disturbances. The mixed H2/H∞tracking performance ensures both robust stability under a prescribed attenuation level for external disturbance and H2optimal tracking. The neural network was introduced to adaptively estimate nonlinear uncertainties, improving the system’s performance under parameter uncertainties as well as obtaining the H2/H∞tracking performance. The simulation shows that the control method performs better even when the system is under large modeling uncertainties and external disturbances.
基金Supported by the National Natural Science Foundation of China （60875055）, the Program for New Century Excellent Talents in University （NCET-06- 0210） and the Natural Science Foundation of Tianjin （08JCZDJC21800）.
文摘This paper proposes a feasible force/position control method for industrial robots utilized for such tasks as grinding, polishing, deburring, and so on. Specifically, an adaptive force/position control strategy is designed in this paper which regulates the contact force between a robot and a workpiece to reach any given set-point exponentially fast, and enables the robot to follow a chosen trajectory simultaneously without requiring prior knowledge of the system parameters. The stability of the closed-loop system is analyzed by Lyapunov techniques. To test the validity of the force/position control method, some simulation results are first collected for the closed-loop system. Furthermore, some experiments are implemented on a 5DOF （degree of freedom） industrial robot for the constructed adaptive force controller. Both simulation and experiment results demonstrate the superior performance of the designed adaptive force/position control strategy.
基金Supported by the National Defence Science & Technology Pre-research Fund of China.
文摘A hybrid position/force controller is designed for the joint 2 and the joint 3 of thePUMA 560 robot.The hybrid controller includes a multilayered neural network,which canidentify the dynamics of the contacted environment and can optimize the parameters of PIDcontroller.The experimental results show that after having been trained,the robot has sta-ble response to the training patterns and strong adaptive ability to the situation between thepatterns.
文摘A simple robust scheme of parallel force/position control is proposed in this paper to deal with two problems for non-planar constraint surface and nonlinear mechanical feature of environment： i） uncertainties in environment that are usually not available or difficult to be determined in most practical situations; ii） stability problem or/and integrator windup due to the integration of force error in the force dominance rule in parallel force/position control. It shows that this robust scheme is a good alternative for anti-windup. In the presence of environment uncertainties, global asymptotic stability of the resulting closed-loop system is guaranteed; it environment with complex characteristics. Finally, numerical robot manipulator. also shows robustness of the proposed controller to uncertain simulation verifies results via contact task of a two rigid-links
基金Project supported by the Science and Technology Stress Projects of Hebei Province, China (Grant No 07213526)
文摘Collision avoidance is always difficult in the planning path for a mobile robot. In this paper, the virtual force field between a mobile robot and an obstacle is formed and regulated to maintain a desired distance by hybrid force control algorithm. Since uncertainties from robot dynamics and obstacle degrade the performance of a collision avoidance task, intelligent control is used to compensate for the uncertainties. A radial basis function （RBF） neural network is used to regulate the force field of an accurate distance between a robot and an obstacle in this paper and then simulation studies are conducted to confirm that the proposed algorithm is effective.
文摘Force control based on neural networks is presented. Under the framework of hybrid control, an RBF neural network is used to compensate for all the uncertainties from robot dynamics and unknown environment first. The technique will improve the adaptability to environment stiffness when the end-effector is in contact with the environment, and does not require any a priori knowledge on the upper bound of syste uncertainties. Moreover, it need not compute the inverse of inertia matrix. Learning algorithms for neural networks to minimize the force error directly are designed. Simulation results have shown a better force/position tracking when neural network is used.
基金Supported by Beijing Science Foundation(4122065)National High Technology Research and Development Program of China("863" Program)(2011AA040202)National Science Foundation for Distinguished Young Scholar(60925014)
文摘Antarctic scientific expedition has important strategic significance. It is an inevitable trend to apply robots to assist researchers during the Antarctic expedition. However, the robot manipula- tors at present have a series of problems and unable to meet the requirements of the Antarctic expe- dition. In this paper, a novel Antarctic modular robot manipulator is proposed, which has a compact structure with modular joints. The robot manipulator has high reliability, and quick assembling-and- disassembling ability. Through well wires arranging and thermal controlling, the manipulator can better adapt to the Antarctic environment. In addition, the work space of the manipulator is serious- ly analyzed, and a new hybrid position/force control method is adopted to make the manipulator per- form better. Simulation results validate the control method and show that the robot manipulator has a good performance to meet the requirements of Antarctic expedition.
基金the National Natural Science Foundation of China(Grant Nos.51305384 and 52075466)。
文摘In order to overcome the shortcomings of the traditional sling suspension method,such as complex structure of suspension truss,large running resistance,and low precision of position servo system,a gravity compensation method of lunar rover based on the combination of active suspension and active position following of magnetic levitation is proposed,and the overall design is carried out.The dynamic model of the suspension module of microgravity compensation system was established,and the decoupling control between the constant force component and the position servo component was analyzed and verified.The constant tension control was achieved by using hybrid force/position control.The position following control was realized by using fuzzy adaptive PID(proportional⁃integral⁃differential)control.The stable suspension control was realized based on the principle of force balance.The simulation results show that the compensation accuracy of constant tension could reach more than 95%,the position deviation was less than 5 mm,the position deviation angle was less than 0.025°,and the air gap recovered stability within 0.1 s.The gravity compensation system has excellent dynamic performance and can meet the requirements of microgravity simulation experiment of lunar rover.
