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In virtual reality (VR)-based telerobotic systems, system performance depends highly on the accuracy of the virtual model constructed at the master site. However, state errors between virtual and slave system exist inevitably due to unknown environment parameters and random time delay of communication media. A popular strategy to tackle the problem is by means of virtual environment technology, in which the environment impedance is estimated on slave site and transmitted and recreated as a virtual environment on master site, and then, the virtual model is updated on the fly according to estimated parameters from slave site. As distinct from the existing parameter estimation methods, this article tries to synchronize master and slave sites of telerobotic systems with an Internet one way time delay (OWTD) jitter prediction approach. A virtual manipulator system is constructed as the slave system and can be controlled with an identical virtual manipulator model displayed on the screen of the master site, which is corrected and updated according to historical commands transmitted to the slave site and Internet OWTD jitter prediction results. Three prediction algorithms for time series prediction, i.e., multiple linear regression (MLR), grey model (GM), and autoregressive moving average model (ARMA), are adopted during the implementation of the proposed approach. The developed approach has been validated with a teleoperated free motion task and experimental results indicate that the proposed approach can be used to synchronize master and slave sites and ARMA outperforms GM and MLR in Internet OWTD jitter prediction.

It has been noted that human operating skills had a great impact on performance of human-machine systems. Cognitive behaviors of human operators have been naturally considered as important research contents and have received more and more concern from academia. Research on human cognitive behaviors plays an important role in development of autonomous mechatronic systems and progress in rehabilitation engineering. This paper concerns the design and implementation of a human-machine interaction system on which EEG signals and behavior data can be recorded simultaneously. On this platform, we can set different operating conditions under which operators perform the human-machine interaction tasks, such as the size of time-delay, different multimedia feedback, and etc. This work establishes the foundation for research on cognitive behaviors of human operators in human-machine interaction systems and neural control systems.

This paper proposes a method for balancing a virtual inverted pendulum through Internet based on the prediction of jitter of Internet one-way time delay. The sparse multivariate linear regression method is used to give prediction on Internet time delay jitter. The remote virtual pendulum can be controlled with an identical virtual pendulum model displayed on the screen of the master site, which is updated according to historical commands transmitted to the slave site and Internet jitter prediction results. In the experiments, operators succeed in balancing the remote virtual pendulum through the Internet, which demonstrate the effectiveness and prospect of the proposed Internet based control method.

Internet random time delay constitutes a major challenge for Internet-based teleoperation systems. Since the uncertain time delay may degrade the system performance, and even lead to instability. Although large-scale research works have been conducted on the understanding, testing, and analysis of Internet round trip time delay (RTT), it is not appropriate to use RTT in control methods design. It is well known that control commands arrive at the slave site in an aperiodic manner as a result of Internet random time delay. The subsequent control command will terminate the execution of the current command. Consequently, we will get precise information for slave system once the time delay jitter can be known in advance. This paper proposes a novel research idea for Internet-based teleoperation system from the point of view of delay jitter prediction. Statistical properties of the time delay jitter are investigated. Furthermore, the sparse multivariate linear regression method is used to give prediction on Internet time delay jitter. Simulation results demonstrate that sparse multivariate linear regressive method gives a precise prediction, which indicates that the proposed control method based on Internet time delay jitter has a broad prospect in teleoperation systems.

The cognitive behavior of human operators in human-machine system has long served as a compelling target for control theory. For this purpose, extensive research effort has been focused on the manual control of inverted pendulum, from which cognitive and motor behavior can be obtained. However, much less attention has been paid to the effect on this experimental platform with different input, e.g. force, velocity, and position input. With the intention to provide more interactive form between human operators and electromechanical systems, this manuscript gives a comparative study on a virtual pendulum system which is built based on OpenGL when different commands are provided with a joystick. All forms of dynamical models have been obtained though mathematical manipulation. In order to obtain more realistic effect, dynamical models are solved with Runge-kutta method. A joystick interface enables operators to control the pendulum manually, providing a fun experience. This study establishes the foundation for further research on cognitive behavior of human operators in human-machine interaction systems and neural control systems.

Human motor and cognitive behavior has been considered as an important research content and received increased attention from academia. As a suitable platform, the inverted pendulum under manual control has been studied extensively, since the inverted pendulum is essentially a nonlinear system and strong coupling exists between the human operator and pendulum system. However, performance of the system when feedback force is provided has not been reported. This paper presents a virtual pendulum system which is built based on OpenGL, while control inputs are provided with a joystick. Dynamical model has been obtained though mathematical manipulation. In order to obtain more realistic effect, dynamical model is solved with Runge-Kutta method. The joystick interface enables operators to control the pendulum manually, providing a fun experience. Comparative experiments have been carried out and the preliminary results confirm the performance difference when force/haptic information is provided to the operator. This study establishes the foundation for further research on cognitive behavior of human operators in human-machine interaction systems and neural control systems.

User clustering-based Web service discovery method is presented to deal with lower efficiency of query in current Web service discovery methods. In order to solve this problem, by analyzing the characteristics of Web service and user, get the conclusion that user with similar interest will be interested in similar services. Therefore, by clustering users and establishing recommendation service library, can recommend the service to the user. And a QoS matching is added to satisfy the need of QoS. Experimental results showed that this method is effective and is able to increase the preciseness and ensure the QoS.

Because of the traditional BP neural network's limitation, including easily falling into local minimum, slow convergence and iteration for a long time, we propose a diagnostic system of mental disorders based on Levenberg-Marquardt algorithm. This article illustrates the basic principles of the neural network algorithm and establishes a mental diagnosis model based on L-M algorithm which uses common mental illness among college students as subjects. The outcome of the simulation illustrates the fact that it is effective to apply the neural network to establish a mental diagnostic system because it has reduced the training iterations and training period and it has high accuracy as well.

As a main type of agricultural robot, fruit harvesting robot has a great potential in agriculture production. In this context, a formulation of the manipulator based on Danevit - Hartenberg is educed for the kinematics equation, and the virtual model of manipulator is developed. The kinematics is studied and inverse kinematics is obtained based on algebraic method. The kinematics simulation of the manipulator based on ADAMS is presented. And the kinematics simulation produced the processing motion course and relevant kinematics curves. The results indicate that the manipulator could implement the process according to the expected trajectory successfully.

Telepresence is a critical problem in robotic teleoperation systems. For the sake of collision avoidance between the end-effecter and the object, the human operator has to make close observations on the visual information. This overloads the visual sense of the human operator. On the other hand, there are some potential obstacles in gathering vision information. As a result, the advance notice of collision might be missed or neglected. In order to settle this issue, a virtual force guided control method for robotic teleoperation system is proposed in this paper. This approach combines position-force command strategy and virtual force feedback to perform proper operations, where the virtual force is generated by transforming visual information into reflective force. This control approach improves the operability of teleoperation system and enhances the effectiveness. Experiments are conducted and demonstrate the effectiveness of the virtual force guided control method.

The working space of manipulator is an important dynamic index. Exact computation of the boundary shape and volume or area of the manipulator workspace is very important for its optimum design and application. The workspace should cover the harvesting fruit distribution space of one plant. In this paper, the kinematic model of the manipulator is presented and Monte Carlo method is used to generate a 4-DOF manipulator workspace. As a random sampling numerical method, the Monte Carlo method is relatively simple and flexible to apply, so it is suitable for the workspace generation of the manipulator. Simulation graph is obtained with the aid of arithmetic procedure and computer graphical. Simulation result shows that the manipulator's working space is well-knit and this method is feasible and practical.

Conventional methods are particularly difficult to control wheeled mobile robot because the control approaches require precise models of the system and the environment. To enhance flexibility of control system of wheeled mobile robots, hybrid system frameworks which consider simultaneously the control and decision-making issues are required. In this paper, we model hybrid system using hybrid automata: through analyzing the control process, discrete state set for wheeled mobile robot positioning is set up; transition conditions among discrete states are defined; kinetic equations corresponding to each discrete state are established. This method is particularly useful in modeling the interactions between discrete and continuous components that exist simultaneously in robotic systems. Simulation results verify the validity of this method.

In this paper, a dynamic path planning scheme based on genetic algorithm (GA) is presented for navigation and obstacle avoidance of mobile robot under unknown environment. The real coding, fitness function and specific genetic operators are devised in the algorithm. The unique coding technique decreases the conventional computational complexity of genetic algorithm. It also speeds up the execution of searching by projecting two dimensional data to one dimensional data, which reduce the size of search space. The fitness function of genetic algorithm takes full consideration of three factors: the collision avoidance path, the shortest distance and smoothness of the path. The specific genetic operators are also selected to make the genetic algorithm more effective. The simulation experiments are made under the VC++ 6.0 environment. The simulation results verify that the genetic algorithm is high effective under various complex dynamic environments.

Detailed analysis is given to kinematics of a humanoid robot manipulator. Forward and inverse kinematics of the robot manipulator is performed through Denevit and Hartenberg method. Geometry transformation and square transformation methods are put forward in order to separate joint variables from kinematic equations and kinematics equations are obtained, whereupon mathematic formulas are provided for humanoid robot manipulator control. Simulation results verify the effectiveness of kinematics equations.

This article addresses the hybrid control method for wheeled mobile robot in constrained environment. Wheeled mobile robots, which are characterized by nonholonomic constraints, are particularly difficult to control since environment constraints should be taken into account sometimes. Traditional control methods, which are based on precise models of environment, may lead to great challenges in determining suitable control laws to steer wheeled mobile robots. To enhance autonomy of wheeled mobile robots, hybrid system frameworks which consider simultaneously the control and decision-making issues are required. In this paper, the wheeled mobile robot which operates in a constrained environment is modeled as a 3-layered hybrid architecture: finite state machine for the decision-making process, wheeled mobile robot system for the continuous state plant, while the interface as the interaction between the continuous dynamics and the decision-making process. It is obvious that this hybrid architecture is particularly useful in describing the interactions between discrete and continuous components that exist simultaneously in robotic systems. Simulation results show that the proposed method is effective for the control of wheeled mobile robots.