Vision-based pose stabilization of nonholonomic mobile robots has received extensive attention. At present, most of the solutions of the problem do not take the robot dynamics into account in the controller design, so...Vision-based pose stabilization of nonholonomic mobile robots has received extensive attention. At present, most of the solutions of the problem do not take the robot dynamics into account in the controller design, so that these controllers are difficult to realize satisfactory control in practical application. Besides, many of the approaches suffer from the initial speed and torque jump which are not practical in the real world. Considering the kinematics and dynamics, a two-stage visual controller for solving the stabilization problem of a mobile robot is presented, applying the integration of adaptive control, sliding-mode control, and neural dynamics. In the first stage, an adaptive kinematic stabilization controller utilized to generate the command of velocity is developed based on Lyapunov theory. In the second stage, adopting the sliding-mode control approach, a dynamic controller with a variable speed function used to reduce the chattering is designed, which is utilized to generate the command of torque to make the actual velocity of the mobile robot asymptotically reach the desired velocity. Furthermore, to handle the speed and torque jump problems, the neural dynamics model is integrated into the above mentioned controllers. The stability of the proposed control system is analyzed by using Lyapunov theory. Finally, the simulation of the control law is implemented in perturbed case, and the results show that the control scheme can solve the stabilization problem effectively. The proposed control law can solve the speed and torque jump problems, overcome external disturbances, and provide a new solution for the vision-based stabilization of the mobile robot.展开更多
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
With the increasing number of human-robot interaction applications, robot control characteristics and their effects on safety as well as performance should be taken account into the robot control system. In this paper...With the increasing number of human-robot interaction applications, robot control characteristics and their effects on safety as well as performance should be taken account into the robot control system. In this paper, a position and torque switching con- trol method was proposed to improve the robot safety and performance, when robots and humans work in the same space. The switch- ing control method includes two modes, the position control mode using a proportion-integral （PI） algorithm, and the torque control mode using sliding mode control （SMC） algorithm for eliminating swing. Under the normal condition, the robot works in position con- trol mode for trajectory tracking with quick response. Once the robot and human collide, the robot will switch to torque control mode immediately, and the impact force will be restricted within a safe range. When the robot and human detach, the robot will resume to po- sition control mode automatically. Moreover, for a better performance, the joint torque is detected fl＇om direct-current （DC） motor＇s cur- rent rather than the torque sensor. The experiment results show that the proposed approach is effective and feasible.展开更多
The paper introduces an electroencephalography(EEG) driven online position control scheme for a robot arm by utilizing motor imagery to activate and error related potential(ErrP) to stop the movement of the individual...The paper introduces an electroencephalography(EEG) driven online position control scheme for a robot arm by utilizing motor imagery to activate and error related potential(ErrP) to stop the movement of the individual links, following a fixed(pre-defined) order of link selection. The right(left)hand motor imagery is used to turn a link clockwise(counterclockwise) and foot imagery is used to move a link forward. The occurrence of ErrP here indicates that the link under motion crosses the visually fixed target position, which usually is a plane/line/point depending on the desired transition of the link across 3D planes/around 2D lines/along 2D lines respectively. The imagined task about individual link's movement is decoded by a classifier into three possible class labels: clockwise, counterclockwise and no movement in case of rotational movements and forward, backward and no movement in case of translational movements. One additional classifier is required to detect the occurrence of the ErrP signal, elicited due to visually inspired positional link error with reference to a geometrically selected target position. Wavelet coefficients and adaptive autoregressive parameters are extracted as features for motor imagery and ErrP signals respectively. Support vector machine classifiers are used to decode motor imagination and ErrP with high classification accuracy above 80%. The average time taken by the proposed scheme to decode and execute control intentions for the complete movement of three links of a robot is approximately33 seconds. The steady-state error and peak overshoot of the proposed controller are experimentally obtained as 1.1% and4.6% respectively.展开更多
In this study,a simple position synchronization control algorithm based on an integral sliding mode is developed for dualarm robotic manipulator systems.A first-order sliding surface is designed using cross-coupling e...In this study,a simple position synchronization control algorithm based on an integral sliding mode is developed for dualarm robotic manipulator systems.A first-order sliding surface is designed using cross-coupling error in order to ensure position synchronization of dual-arm manipulators.The design objective of the proposed controller is to ensure stability as well as to synchronize the movement of both arms while maintaining the trajectory as desired.The integral sliding mode eliminates the reaching phase and guarantees robustness throughout the whole operating period.Additionally,a low pass filter is used to smoothen the discontinuous element and minimize unwanted chattering.Lyapunov stability theory is utilized to prove the asymptotic stability of the controlled system.Simulation studies are performed to validate the proposed controller′s effectiveness.Also,to investigate the possibility of realizing the proposed dynamic control method in practical applications,experiments are conducted on a 14DoF coordinated links(COOL)dual-arm robotic manipulator system.Experimental evidence indicates adequate efficiency in trajectory tracking and guarantees robustness in the presence of parametric uncertainty and external disturbance.展开更多
This work presents a controller designed for position-controlled quadrupedal dynamic locomotion,aiming at simple and robust trotting control. The controller takes the torso attitude angles and velocities into planning...This work presents a controller designed for position-controlled quadrupedal dynamic locomotion,aiming at simple and robust trotting control. The controller takes the torso attitude angles and velocities into planning foot trajectories. Firstly design of the servo motor actuated quadruped robot is introduced and the kinematic equations are deduced. Then a scheme is presented for controlling the robot torso attitude based on the virtual leg model. Furthermore,it demonstrates the design of the controller which enables the robot to have a wide range of trotting gaits and omni-directional motions. Finally,results of robust trotting in various speeds,path tracking and push recovery in simulation are reported,and results of trotting on real quadruped robots will be studied.展开更多
This paper proposes robot position control using force information for cooperative work between two remote robot systems with force feedback in each of which a user operates a remote robot by using a haptic interface ...This paper proposes robot position control using force information for cooperative work between two remote robot systems with force feedback in each of which a user operates a remote robot by using a haptic interface device while observing work of the robot with a video camera. We also investigate the effect of the proposed control by experiment. As cooperative work, we deal with work in which two robots carry an object together. The robot position control using force information finely adjusts the position of the robot arm to reduce the force applied to the object. Thus, the purpose of the control is to avoid large force so that the object is not broken. In our experiment, we make a comparison among the following three cases in order to clarify how to carry out the control effectively. In the first case, the two robots are operated manually by a user with his/her both hands. In the second case, one robot is operated manually by a user, and the other robot is moved automatically under the proposed control. In the last case, the object is carried directly by a human instead of the robot which is operated by the user in the second case. As a result, experimental results demonstrate that the control can help each system operated manually by the user to carry the object smoothly.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
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
Compared with wheeled or tracked robots,legged robots exhibit advantages on agile locomotion and higher survival chance for deadly impacts. A buffering strategy is proposed for quadruped robots with non-extreme initia...Compared with wheeled or tracked robots,legged robots exhibit advantages on agile locomotion and higher survival chance for deadly impacts. A buffering strategy is proposed for quadruped robots with non-extreme initial attitudes from the end of air-righting to the steady standing on the ground.This approach consists of landing phase,buffering phase and recovering phase. The variable stiffness control,proportional-derivative( PD) force control and foot trajectory planning are applied to the joints of quadruped robots until the end of the recovering phase. The PD parameters are tuned according to the desired performance of each phase. The above approach is verified on a virtual platform.展开更多
Robotic belt grinding has emerged as a finishing process in recent years for machining components with high surface finish and flexibility.The surface machining consistency,however,is difficult to be guaranteed in suc...Robotic belt grinding has emerged as a finishing process in recent years for machining components with high surface finish and flexibility.The surface machining consistency,however,is difficult to be guaranteed in such a process.To overcome this problem,a method of hybrid force-position control combined with PI/PD control is proposed to be applied in robotic abrasive belt grinding of complex geometries.Voltage signals are firstly obtained and transformed to force information with signal conditioning methods.Secondly,zero drift and gravity compensation algorithms are presented to calibrate the F/T transducer which is installed on the robot end-effector.Next,a force control strategy combining hybrid force-position control with PI/PD control is introduced to be employed in robotic abrasive belt grinding operations where the force control law is applied to the Z direction of the tool frame and the positon control law is used in the X direction of the tool frame.Then,the accuracy of the F/T transducer and the robotic force control system is analyzed to ensure the stability and reliability of force control in the robotic grinding process.Finally,two typical cases on robotic belt grinding of a test workpiece and an aero-engine blade are conducted to validate the practicality and effectiveness of the force control technology proposed.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
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
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
The development of human-robot interaction has been continu-ously increasing for the last decades.Through this development,it has become simpler and safe interactions using a remotely controlled telepresence robot in ...The development of human-robot interaction has been continu-ously increasing for the last decades.Through this development,it has become simpler and safe interactions using a remotely controlled telepresence robot in an insecure and hazardous environment.The audio-video communication connection or data transmission stability has already been well handled by fast-growing technologies such as 5G and 6G.However,the design of the phys-ical parameters,e.g.,maneuverability,controllability,and stability,still needs attention.Therefore,the paper aims to present a systematic,controlled design and implementation of a telepresence mobile robot.The primary focus of this paper is to perform the computational analysis and experimental implementa-tion design with sophisticated position control,which autonomously controls the robot’s position and speed when reaching an obstacle.A system model and a position controller design are developed with root locus points.The design robot results are verified experimentally,showing the robot’s agreement and control in the desired position.The robot was tested by considering various parameters:driving straight ahead,right turn,self-localization and complex path.The results prove that the proposed approach is flexible and adaptable and gives a better alternative.The experimental results show that the proposed method significantly minimizes the obstacle hits.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
The dynamics properties of a kind of multi-fingered robot hand is analyzed. It is pointed out that the dynamics property of this kind of multifingered robot hand in the approaching process is quite different from that...The dynamics properties of a kind of multi-fingered robot hand is analyzed. It is pointed out that the dynamics property of this kind of multifingered robot hand in the approaching process is quite different from that in the grasping process and,different control algorithm should be taken in the two process. A position-force hybrid control algorithm is proposed which is applied to the control system of the University of Science and Technology Beijing double-thumb robot hand successfully.展开更多
Tendon-driven robots have distinct advantages in high-dynamic performance motion and high-degree-of-freedom manipulation.However,these robots face challenges related to control complexity,intricate tendon drive paths,...Tendon-driven robots have distinct advantages in high-dynamic performance motion and high-degree-of-freedom manipulation.However,these robots face challenges related to control complexity,intricate tendon drive paths,and tendon slackness.In this study,the authors present a novel modular tendon-driven actuator design that integrates a series elastic element.The actuator incorporates a unique magnetic position sensing technology that enables observation of the length and tension of the tendon and features an exceptionally compact design.The modular architecture of the tendon-driven actuator addresses the complexity of tendon drive paths,while the tension observation functionality mitigates slackness issues.The design and modeling of the actuator are described in this paper,and a series of tests are conducted to validate the simulation model and to test the performance of the proposed actuator.The model can be used for training robot control neural networks based on simulation,thereby overcoming the challenges associated with controlling tendon-driven robots.展开更多
基金supported by National Key Basic Research and Development Program of China (973 Program,Grant No. 2009CB320602)National Natural Science Foundation of China (Grant Nos. 60834004,61025018)+2 种基金National Science and Technology Major Project of China(Grant No. 2011ZX02504-008)Fundamental Research Funds for the Central Universities of China (Grant No. ZZ1222)Key Laboratory of Advanced Engineering Surveying of NASMG of China (Grant No.TJES1106)
文摘Vision-based pose stabilization of nonholonomic mobile robots has received extensive attention. At present, most of the solutions of the problem do not take the robot dynamics into account in the controller design, so that these controllers are difficult to realize satisfactory control in practical application. Besides, many of the approaches suffer from the initial speed and torque jump which are not practical in the real world. Considering the kinematics and dynamics, a two-stage visual controller for solving the stabilization problem of a mobile robot is presented, applying the integration of adaptive control, sliding-mode control, and neural dynamics. In the first stage, an adaptive kinematic stabilization controller utilized to generate the command of velocity is developed based on Lyapunov theory. In the second stage, adopting the sliding-mode control approach, a dynamic controller with a variable speed function used to reduce the chattering is designed, which is utilized to generate the command of torque to make the actual velocity of the mobile robot asymptotically reach the desired velocity. Furthermore, to handle the speed and torque jump problems, the neural dynamics model is integrated into the above mentioned controllers. The stability of the proposed control system is analyzed by using Lyapunov theory. Finally, the simulation of the control law is implemented in perturbed case, and the results show that the control scheme can solve the stabilization problem effectively. The proposed control law can solve the speed and torque jump problems, overcome external disturbances, and provide a new solution for the vision-based stabilization of the mobile robot.
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supported by National Natural Science Foundation of China(Nos.51175084,51575111 and 51605093)Fujian Province Natural Science Foundation(No.2015J05121)Fuzhou University-Enterprise Cooperation Project(No.2015H6012)
文摘With the increasing number of human-robot interaction applications, robot control characteristics and their effects on safety as well as performance should be taken account into the robot control system. In this paper, a position and torque switching con- trol method was proposed to improve the robot safety and performance, when robots and humans work in the same space. The switch- ing control method includes two modes, the position control mode using a proportion-integral （PI） algorithm, and the torque control mode using sliding mode control （SMC） algorithm for eliminating swing. Under the normal condition, the robot works in position con- trol mode for trajectory tracking with quick response. Once the robot and human collide, the robot will switch to torque control mode immediately, and the impact force will be restricted within a safe range. When the robot and human detach, the robot will resume to po- sition control mode automatically. Moreover, for a better performance, the joint torque is detected fl＇om direct-current （DC） motor＇s cur- rent rather than the torque sensor. The experiment results show that the proposed approach is effective and feasible.
基金supported by UGC Sponsored UPE-ⅡProject in Cognitive Science of Jadavpur University,Kolkata
文摘The paper introduces an electroencephalography(EEG) driven online position control scheme for a robot arm by utilizing motor imagery to activate and error related potential(ErrP) to stop the movement of the individual links, following a fixed(pre-defined) order of link selection. The right(left)hand motor imagery is used to turn a link clockwise(counterclockwise) and foot imagery is used to move a link forward. The occurrence of ErrP here indicates that the link under motion crosses the visually fixed target position, which usually is a plane/line/point depending on the desired transition of the link across 3D planes/around 2D lines/along 2D lines respectively. The imagined task about individual link's movement is decoded by a classifier into three possible class labels: clockwise, counterclockwise and no movement in case of rotational movements and forward, backward and no movement in case of translational movements. One additional classifier is required to detect the occurrence of the ErrP signal, elicited due to visually inspired positional link error with reference to a geometrically selected target position. Wavelet coefficients and adaptive autoregressive parameters are extracted as features for motor imagery and ErrP signals respectively. Support vector machine classifiers are used to decode motor imagination and ErrP with high classification accuracy above 80%. The average time taken by the proposed scheme to decode and execute control intentions for the complete movement of three links of a robot is approximately33 seconds. The steady-state error and peak overshoot of the proposed controller are experimentally obtained as 1.1% and4.6% respectively.
文摘In this study,a simple position synchronization control algorithm based on an integral sliding mode is developed for dualarm robotic manipulator systems.A first-order sliding surface is designed using cross-coupling error in order to ensure position synchronization of dual-arm manipulators.The design objective of the proposed controller is to ensure stability as well as to synchronize the movement of both arms while maintaining the trajectory as desired.The integral sliding mode eliminates the reaching phase and guarantees robustness throughout the whole operating period.Additionally,a low pass filter is used to smoothen the discontinuous element and minimize unwanted chattering.Lyapunov stability theory is utilized to prove the asymptotic stability of the controlled system.Simulation studies are performed to validate the proposed controller′s effectiveness.Also,to investigate the possibility of realizing the proposed dynamic control method in practical applications,experiments are conducted on a 14DoF coordinated links(COOL)dual-arm robotic manipulator system.Experimental evidence indicates adequate efficiency in trajectory tracking and guarantees robustness in the presence of parametric uncertainty and external disturbance.
基金Supported by the National Natural Science Foundation of China(No.61233014,61305130)China Postdoctoral Science Foundation(No.2013M541912)the Shandong Provincial Natural Science Foundation(No.ZR2013FQ003,ZR2013EEM027)
文摘This work presents a controller designed for position-controlled quadrupedal dynamic locomotion,aiming at simple and robust trotting control. The controller takes the torso attitude angles and velocities into planning foot trajectories. Firstly design of the servo motor actuated quadruped robot is introduced and the kinematic equations are deduced. Then a scheme is presented for controlling the robot torso attitude based on the virtual leg model. Furthermore,it demonstrates the design of the controller which enables the robot to have a wide range of trotting gaits and omni-directional motions. Finally,results of robust trotting in various speeds,path tracking and push recovery in simulation are reported,and results of trotting on real quadruped robots will be studied.
文摘This paper proposes robot position control using force information for cooperative work between two remote robot systems with force feedback in each of which a user operates a remote robot by using a haptic interface device while observing work of the robot with a video camera. We also investigate the effect of the proposed control by experiment. As cooperative work, we deal with work in which two robots carry an object together. The robot position control using force information finely adjusts the position of the robot arm to reduce the force applied to the object. Thus, the purpose of the control is to avoid large force so that the object is not broken. In our experiment, we make a comparison among the following three cases in order to clarify how to carry out the control effectively. In the first case, the two robots are operated manually by a user with his/her both hands. In the second case, one robot is operated manually by a user, and the other robot is moved automatically under the proposed control. In the last case, the object is carried directly by a human instead of the robot which is operated by the user in the second case. As a result, experimental results demonstrate that the control can help each system operated manually by the user to carry the object smoothly.
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.
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 High Technology Research and Development Program of China(No.2015AA042201)the National Natural Science Foundation of China(No.61233014,61305130)+1 种基金the Shandong Provincial Natural Science Foundation(No.ZR2013FQ003,ZR2013EEM027)China Postdoctoral Science Foundation(No.2013M541912)
文摘Compared with wheeled or tracked robots,legged robots exhibit advantages on agile locomotion and higher survival chance for deadly impacts. A buffering strategy is proposed for quadruped robots with non-extreme initial attitudes from the end of air-righting to the steady standing on the ground.This approach consists of landing phase,buffering phase and recovering phase. The variable stiffness control,proportional-derivative( PD) force control and foot trajectory planning are applied to the joints of quadruped robots until the end of the recovering phase. The PD parameters are tuned according to the desired performance of each phase. The above approach is verified on a virtual platform.
基金National Nature Science Foundation of China(Nos.51675394and 51375196)National Key Research and Development Program of China(No.2017YFB1303404)+2 种基金State Key Laboratory of Digital Manufacturing Equipment and Technology of China(No.DMETKF2018018)Fundamental Research Funds for the Central Universities of China(No.2017II33GX)the Key R&D Program of Jiangsu Province(No.BE2015005)
文摘Robotic belt grinding has emerged as a finishing process in recent years for machining components with high surface finish and flexibility.The surface machining consistency,however,is difficult to be guaranteed in such a process.To overcome this problem,a method of hybrid force-position control combined with PI/PD control is proposed to be applied in robotic abrasive belt grinding of complex geometries.Voltage signals are firstly obtained and transformed to force information with signal conditioning methods.Secondly,zero drift and gravity compensation algorithms are presented to calibrate the F/T transducer which is installed on the robot end-effector.Next,a force control strategy combining hybrid force-position control with PI/PD control is introduced to be employed in robotic abrasive belt grinding operations where the force control law is applied to the Z direction of the tool frame and the positon control law is used in the X direction of the tool frame.Then,the accuracy of the F/T transducer and the robotic force control system is analyzed to ensure the stability and reliability of force control in the robotic grinding process.Finally,two typical cases on robotic belt grinding of a test workpiece and an aero-engine blade are conducted to validate the practicality and effectiveness of the force control technology proposed.
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
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.
基金supported by the Deanship of Scientific Research at Prince Sattam bin Abdulaziz University under the research project (PSAU/2023/01/23001).
文摘The development of human-robot interaction has been continu-ously increasing for the last decades.Through this development,it has become simpler and safe interactions using a remotely controlled telepresence robot in an insecure and hazardous environment.The audio-video communication connection or data transmission stability has already been well handled by fast-growing technologies such as 5G and 6G.However,the design of the phys-ical parameters,e.g.,maneuverability,controllability,and stability,still needs attention.Therefore,the paper aims to present a systematic,controlled design and implementation of a telepresence mobile robot.The primary focus of this paper is to perform the computational analysis and experimental implementa-tion design with sophisticated position control,which autonomously controls the robot’s position and speed when reaching an obstacle.A system model and a position controller design are developed with root locus points.The design robot results are verified experimentally,showing the robot’s agreement and control in the desired position.The robot was tested by considering various parameters:driving straight ahead,right turn,self-localization and complex path.The results prove that the proposed approach is flexible and adaptable and gives a better alternative.The experimental results show that the proposed method significantly minimizes the obstacle hits.
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.
文摘The dynamics properties of a kind of multi-fingered robot hand is analyzed. It is pointed out that the dynamics property of this kind of multifingered robot hand in the approaching process is quite different from that in the grasping process and,different control algorithm should be taken in the two process. A position-force hybrid control algorithm is proposed which is applied to the control system of the University of Science and Technology Beijing double-thumb robot hand successfully.
基金supported in part by the National Key R&D Program of China under Grant 2024YFB4707900the National Natural Science Foundation of China under Grant 91948302 and Grant 52021003.
文摘Tendon-driven robots have distinct advantages in high-dynamic performance motion and high-degree-of-freedom manipulation.However,these robots face challenges related to control complexity,intricate tendon drive paths,and tendon slackness.In this study,the authors present a novel modular tendon-driven actuator design that integrates a series elastic element.The actuator incorporates a unique magnetic position sensing technology that enables observation of the length and tension of the tendon and features an exceptionally compact design.The modular architecture of the tendon-driven actuator addresses the complexity of tendon drive paths,while the tension observation functionality mitigates slackness issues.The design and modeling of the actuator are described in this paper,and a series of tests are conducted to validate the simulation model and to test the performance of the proposed actuator.The model can be used for training robot control neural networks based on simulation,thereby overcoming the challenges associated with controlling tendon-driven robots.
