A new visual servo control scheme for a robotic manipulator is presented in this paper, where a back propagation （BP） neural network is used to make a direct transition from image feature to joint angles without req...A new visual servo control scheme for a robotic manipulator is presented in this paper, where a back propagation （BP） neural network is used to make a direct transition from image feature to joint angles without requiring robot kinematics and camera calibration. To speed up the convergence and avoid local minimum of the neural network, this paper uses a genetic algorithm to find the optimal initial weights and thresholds and then uses the BP Mgorithm to train the neural network according to the data given. The proposed method can effectively combine the good global searching ability of genetic algorithms with the accurate local searching feature of BP neural network. The Simulink model for PUMA560 robot visual servo system based on the improved BP neural network is built with the Robotics Toolbox of Matlab. The simulation results indicate that the proposed method can accelerate convergence of the image errors and provide a simple and effective way of robot control.展开更多
A visual servoing tracking controller is proposed based on the sliding mode control theory in order to achieve strong robustness against parameter variations and external disturbances. A sliding plane with time delay ...A visual servoing tracking controller is proposed based on the sliding mode control theory in order to achieve strong robustness against parameter variations and external disturbances. A sliding plane with time delay compensation is presented by the pre-estimate of states. To reduce the chattering of the sliding mode controller, a modified exponential reaching law and hyperbolic tangent function are applied to the design of visual controller and robot joint controller. Simulation results show that the visual servoing control scheme is robust and has good tracking performance.展开更多
In IBVS (image based visual servoing), the error signal in image space should be transformed into the control signal in the input space quickly. To avoid the iterative adjustment and complicated inverse solution of im...In IBVS (image based visual servoing), the error signal in image space should be transformed into the control signal in the input space quickly. To avoid the iterative adjustment and complicated inverse solution of image Jacobian, CMAC (cerebellar model articulation controller) neural network is inserted into visual servo control loop to implement the nonlinear mapping. Two control schemes are used. Simulation results on two schemes are provided, which show a better tracking precision and stability can be achieved using scheme 2.展开更多
A dual operational modes mobile robot system based on visual guiding and visual servo control is presented. This system consists of a mobile robot with a two-axis manipulator and a tele-operation station. In the visua...A dual operational modes mobile robot system based on visual guiding and visual servo control is presented. This system consists of a mobile robot with a two-axis manipulator and a tele-operation station. In the visual guiding mode, for the robot works in an open loop visual servo control mode, the manipulating burden of the operator is reduced largely. In the visual servo mode the robot can locate the position of the target assigned by the operator and pick it up by its manipulator. With the help of the operator, the diffieuh problems of finding and handling a target in a complicated environment by the robot can be solved easily.展开更多
【目的】针对机器人自主装配研究多聚焦静态目标,移动目标装配相关研究不足的问题,提出一种视觉阻抗控制器的变参数控制方法,以提升机器人在动态环境中目标跟踪与移动装配的适应性和柔顺性。【方法】首先,结合力反馈与视觉反馈信息,在...【目的】针对机器人自主装配研究多聚焦静态目标,移动目标装配相关研究不足的问题,提出一种视觉阻抗控制器的变参数控制方法,以提升机器人在动态环境中目标跟踪与移动装配的适应性和柔顺性。【方法】首先,结合力反馈与视觉反馈信息,在特征空间构建2阶阻抗控制器,为动态装配提供控制基础;其次,将蒙特卡洛随机失活(Monte Carlo Dropout,MCD)作为概率动力学模型,改进概率推理学习控制优化(Probabilistic Inference for Learning Control Optimization,PILCO)算法,平衡状态不确定性推理能力与计算效率;最后,以特征误差和机器人关节位置信息为观测空间,自适应调整控制器阻抗参数,优化动态跟踪与装配性能。【结果】仿真及试验台验证结果表明,相比原高斯过程模型,MCD模型在保留状态不确定性推理能力的同时,显著缩短训练时间(50轮训练时间从43.50 h降至12.82 h);装配成功率从94.5%提升至98.0%,平均装配用时从5.820 s缩短至3.253 s,超调量大幅减少,跟踪响应更及时。研究可为移动目标柔顺装配提供参考。展开更多
Soft robots show remarkable benefits over conventional rigid robots due to their high energy density and other factors. We propose a circular soft robot integrating the control system, actuating it with several shape ...Soft robots show remarkable benefits over conventional rigid robots due to their high energy density and other factors. We propose a circular soft robot integrating the control system, actuating it with several shape memory alloy (SMA) actuators. Our research methodology involved connecting the DC voltage supply and L298N module to provide uninterrupted power to the actuator and thence control the actuator via Arduino Uno MCU and TOF camera. We designed the controller to simultaneously complete the positioning and manipulation tasks. A novel method utilizing visual servo and closed-loop control algorithm was proposed and integrated into the controller. This method involves the implementation of multi-gait locomotion using SMA actuators. Additionally, the development of closed-loop dynamic controllers for a continuous soft robot is also evaluated. The proposed control model is designed and simulated on the MATLAB tool. To verify the efficiency of the proposed forward-feedback controller, simulations and experiments were conducted in the current study. A new control method using PID control based on the Kalman filtering algorithm and visual servo for the SMA actuator designed in this research is introduced. We conclude that applying spike excitation voltage would benefit the actuating performance. Overall, the experimental results demonstrated a promising future for the purposed control method.展开更多
Robot-assisted surgery has become an indispensable component in modern neurosurgical procedures.However,existing registration methods for neurosurgical robots often rely on high-end hardware and involve prolonged or u...Robot-assisted surgery has become an indispensable component in modern neurosurgical procedures.However,existing registration methods for neurosurgical robots often rely on high-end hardware and involve prolonged or unstable registration times,limiting their applicability in dynamic and time-sensitive intraoperative settings.This paper proposes a novel fully automatic monocular-based registration and real-time tracking method.First,dedicated fiducials are designed,and an automatic preoperative and intraoperative detection method for these fiducials is introduced.Second,a geometric representation of the fiducials is constructed based on a 2D KD-Tree.Through a two-stage optimization process,the depth of 2D fiducials is estimated,and 2D-3D correspondences are established to achieve monocular registration.This approach enables fully automatic intraoperative registration using only a single optical camera.Finally,a six-degree-of-freedom visual servo control strategy inspired by the mass-spring-damper system is proposed.By integrating artificial potential field and admittance control,the strategy ensures real-time responsiveness and stable tracking.Experimental results demonstrate that the proposed method achieves a registration time of 0.23 s per instance with an average error of 0.58 mm.Additionally,the motion performance of the control strategy has been validated.Preliminary experiments verify the effectiveness of MonoTracker in dynamic tracking scenarios.This method holds promise for enhancing the adaptability of neurosurgical robots and offers significant clinical application potential.展开更多
文摘A new visual servo control scheme for a robotic manipulator is presented in this paper, where a back propagation （BP） neural network is used to make a direct transition from image feature to joint angles without requiring robot kinematics and camera calibration. To speed up the convergence and avoid local minimum of the neural network, this paper uses a genetic algorithm to find the optimal initial weights and thresholds and then uses the BP Mgorithm to train the neural network according to the data given. The proposed method can effectively combine the good global searching ability of genetic algorithms with the accurate local searching feature of BP neural network. The Simulink model for PUMA560 robot visual servo system based on the improved BP neural network is built with the Robotics Toolbox of Matlab. The simulation results indicate that the proposed method can accelerate convergence of the image errors and provide a simple and effective way of robot control.
基金supported by China Postdoctoral Science Founda-tion (No. 20080441093)Key Laboratory Foundation of Liaoning Province (No. 2008S088).
文摘A visual servoing tracking controller is proposed based on the sliding mode control theory in order to achieve strong robustness against parameter variations and external disturbances. A sliding plane with time delay compensation is presented by the pre-estimate of states. To reduce the chattering of the sliding mode controller, a modified exponential reaching law and hyperbolic tangent function are applied to the design of visual controller and robot joint controller. Simulation results show that the visual servoing control scheme is robust and has good tracking performance.
基金This project is supported by National Natural Science Foundation of China (No.59990470).
文摘In IBVS (image based visual servoing), the error signal in image space should be transformed into the control signal in the input space quickly. To avoid the iterative adjustment and complicated inverse solution of image Jacobian, CMAC (cerebellar model articulation controller) neural network is inserted into visual servo control loop to implement the nonlinear mapping. Two control schemes are used. Simulation results on two schemes are provided, which show a better tracking precision and stability can be achieved using scheme 2.
基金Supported by the National High Technology Research and Development Program of China （No. 2003AA421030） and the National Science Foundation of China （No. 60375026）.
文摘A dual operational modes mobile robot system based on visual guiding and visual servo control is presented. This system consists of a mobile robot with a two-axis manipulator and a tele-operation station. In the visual guiding mode, for the robot works in an open loop visual servo control mode, the manipulating burden of the operator is reduced largely. In the visual servo mode the robot can locate the position of the target assigned by the operator and pick it up by its manipulator. With the help of the operator, the diffieuh problems of finding and handling a target in a complicated environment by the robot can be solved easily.
基金Supported by National Natural Science Foundation of China（60874002） Key Project of Shanghai Education Committee （09ZZ158） Leading Academic Discipline Project of Shanghai Municipal Government （S30501）
文摘【目的】针对机器人自主装配研究多聚焦静态目标,移动目标装配相关研究不足的问题,提出一种视觉阻抗控制器的变参数控制方法,以提升机器人在动态环境中目标跟踪与移动装配的适应性和柔顺性。【方法】首先,结合力反馈与视觉反馈信息,在特征空间构建2阶阻抗控制器,为动态装配提供控制基础;其次,将蒙特卡洛随机失活(Monte Carlo Dropout,MCD)作为概率动力学模型,改进概率推理学习控制优化(Probabilistic Inference for Learning Control Optimization,PILCO)算法,平衡状态不确定性推理能力与计算效率;最后,以特征误差和机器人关节位置信息为观测空间,自适应调整控制器阻抗参数,优化动态跟踪与装配性能。【结果】仿真及试验台验证结果表明,相比原高斯过程模型,MCD模型在保留状态不确定性推理能力的同时,显著缩短训练时间(50轮训练时间从43.50 h降至12.82 h);装配成功率从94.5%提升至98.0%,平均装配用时从5.820 s缩短至3.253 s,超调量大幅减少,跟踪响应更及时。研究可为移动目标柔顺装配提供参考。
文摘Soft robots show remarkable benefits over conventional rigid robots due to their high energy density and other factors. We propose a circular soft robot integrating the control system, actuating it with several shape memory alloy (SMA) actuators. Our research methodology involved connecting the DC voltage supply and L298N module to provide uninterrupted power to the actuator and thence control the actuator via Arduino Uno MCU and TOF camera. We designed the controller to simultaneously complete the positioning and manipulation tasks. A novel method utilizing visual servo and closed-loop control algorithm was proposed and integrated into the controller. This method involves the implementation of multi-gait locomotion using SMA actuators. Additionally, the development of closed-loop dynamic controllers for a continuous soft robot is also evaluated. The proposed control model is designed and simulated on the MATLAB tool. To verify the efficiency of the proposed forward-feedback controller, simulations and experiments were conducted in the current study. A new control method using PID control based on the Kalman filtering algorithm and visual servo for the SMA actuator designed in this research is introduced. We conclude that applying spike excitation voltage would benefit the actuating performance. Overall, the experimental results demonstrated a promising future for the purposed control method.
基金Supported by National Natural Science Foundation of China(Grant No.92148206).
文摘Robot-assisted surgery has become an indispensable component in modern neurosurgical procedures.However,existing registration methods for neurosurgical robots often rely on high-end hardware and involve prolonged or unstable registration times,limiting their applicability in dynamic and time-sensitive intraoperative settings.This paper proposes a novel fully automatic monocular-based registration and real-time tracking method.First,dedicated fiducials are designed,and an automatic preoperative and intraoperative detection method for these fiducials is introduced.Second,a geometric representation of the fiducials is constructed based on a 2D KD-Tree.Through a two-stage optimization process,the depth of 2D fiducials is estimated,and 2D-3D correspondences are established to achieve monocular registration.This approach enables fully automatic intraoperative registration using only a single optical camera.Finally,a six-degree-of-freedom visual servo control strategy inspired by the mass-spring-damper system is proposed.By integrating artificial potential field and admittance control,the strategy ensures real-time responsiveness and stable tracking.Experimental results demonstrate that the proposed method achieves a registration time of 0.23 s per instance with an average error of 0.58 mm.Additionally,the motion performance of the control strategy has been validated.Preliminary experiments verify the effectiveness of MonoTracker in dynamic tracking scenarios.This method holds promise for enhancing the adaptability of neurosurgical robots and offers significant clinical application potential.
