This paper proposes a new predictive control method for the teleoperation in a non-visible environment. The trajectory error caused by the time delay has been compensated by the Smith predictor and the feedback data have been estimated by the Grey model. The Smith predictor is effective for the compensation of the positioning error caused by the time delay of a precise system model. Therefore the dynamic model of a mobile robot has been derived in this research. Through simulations, the errors caused by the time delay has been verified using the Smith predictor. Also the estimation reliability of the measurement data has been demonstrated. Robust teleoperations in a non-visible environment have been performed with a mobile robot to effectively avoid the obstacles in order to reach the target position by the proposed prediction scheme which associates the Smith predictor and the Grey model.

As an extension of the conventional output constraint problem, this paper proposes the use of nonlinear dynamic surface control (DSC) combined with adaptive fuzzy logic control to constrain the partial tracking errors of strict feedback nonlinear dynamic systems with uncertainties. Transformation of the tracking errors into new virtual error variables is used to recursively design a DSC controller, and a careful selection of the controller design parameters ensures that partial state tracking errors are confined at all times within the prescribed bounds. The stability and boundedness of all closed-loop signals were confirmed using the Lyapunov theorem. The simulation results highlight the efficacy and utility of the proposed control scheme.

This paper presents a method for controlling a two-wheeled mobile manipulator with visual servoing. There are three subsystems: stereo vision system, 10 DOF dual arm manipulator and two-wheeled mobile robot. The whole system can be seen as an inverted pendulum. When the robot reaches the stable state, the centroid of the whole system is in the perpendicular line of the central point of mobile robot platform and ground. The target object can be tracked using CamShift algorithm. The size, position of the object, and the distance between the object and mobile manipulator can be obtained with visual servoing. A stereo vision system with image based visual servoing (IBVS) is proposed in this paper.

This article presents the nonlinear dynamics and the posture stabilization control scheme for the single-wheeled pendulum robot (SWPR). Considering the maneuverability of SWPR, the steering is realized through the control for the inertia pendulum (IP) installed horizontally on the middle part of robot body. The feature of the control system modeling consists in a technique for which the posture stabilization control design is based on the parameterization of the dynamic interactions (DIT) between the lateral dynamics, the longitudinal dynamics, and the rotational dynamics. Simulation results showed the feasibility of the SWPR model and the control algorithm.

This paper proposes a beacon color code scheduling algorithm for the localization of multiple robots in a multiblock workspace. With the development of intelligent robotics and ubiquitous technology, service robots are applicable for use in wide areas, such as airports and train stations, where multiple indoor GPS systems are required for the localization of the mobile robots. Indoor localization schemes using ultrasonic sensors have been widely studied due to their cheap price and high accuracy. However, ultrasonic sensors have some disadvantages, such as a short transmission range and interference with other ultrasonic signals. In order to concurrently use multiple robots in wide-area workspaces, it is necessary to resolve the interference problem among the multiple robots in the localization process. This paper proposes an indoor localization system for concurrent multiple robots localization in a wide service area divided into multiblocks for reliable sensor operation. The beacon color code scheduling algorithm is developed in order to avoid signal interference and to achieve an efficient localization with a high accuracy and a short sampling time. The performance of the proposed localization system has been verified through real experiments.

Though the final goal of mobile robot navigation is to be autonomous, operators' intelligent and skillful decisions are necessary when there are many scattered obstacles. There are several limitations even in the camera-based tele-operation of a mobile robot, which is very popular for the mobile robot navigation. For examples, shadowed and curved areas cannot be viewed using a narrow view-angle camera, especially in bad weather such as on snowy or rainy days. Therefore, it is necessary to have other sensory information for reliable tele-operations. In this paper, sixteen ultrasonic sensors are attached around a mobile robot in a ring pattern to measure the distances to obstacles. A collision vector is introduced in this paper as a new tool for obstacle avoidance, which is defined as a normal vector from an obstacle to the mobile robot. Based on this collision vector, a virtual reflection force is generated to avoid the obstacles and then the reflection force is transferred to an operator who is holding a joystick to control the mobile robot. Relying on the reflection force, the operator can control the mobile robot more smoothly and safely. For this bi-directional tele-operation, a master joystick system using a hall sensor was designed to resolve the existence of nonlinear sections, which are usual for a general joystick with two motors and potentiometers. Finally, the efficiency of a force reflection joystick is verified through the comparison of two vision-based tele-operation experiments, with and without force reflection.

The possibility of operating in remote environments by means of teleoperated systems has always been considered of relevant interest in robotics. For this reason, in this paper, the relationship between a slave robot and the uncertain remote environment is proposed as the impedance to generate the virtual force to feed back Io the operator. For the control of a teleoperated mobile robot equipped with camera, the teleoperated mobile robot take pictures of remote environment and sends the visual information back to the operator over the Internet. Because of the limitation of communication bandwidth and narrow view-angles of camera, it is not possible to watch the environment clearly, especially shadow and curved areas. To overcome this problem, the virtual force is generated according to both the distance between the obstacle and robot and the approaching velocity of the obstacle. This virtual force is transferred back to the master over the Internet and the master, which can generate force, enables a human operator to estimate the position of obstacle in the remote environment. By holding this master, in spite of limited visual information, the operator can feel the spatial sense against the remote environment. This force reflection improves the performance of a teleoperated mobile robot significantly.

This paper proposes a sensor-fusion technique where the data sets for the previous moments are properly transformed and fused into the current data sets to enable accurate measurement, such as, distance to an obstacle and location of the service robot itself. In the conventional fusion schemes, the measurement is dependent on the current data sets. As the results, more of sensors are required to measure a certain physical parameter or to improve the accuracy of the measurement. However in this approach, instead of adding more sensors to the system, the temporal sequence of the data sets are stored and utilized for the measurement improvement. Theoretical basis is illustrated by examples and the effectiveness is proved through the simulations. Finally, the new space and time sensor fusion (NSTF) scheme is applied to the control of a mobile robot in an unstructured environment as well as structured environment.

A moving window scheme for detecting lanes and obstacles from the images captured by a CCD camera in an automobile is proposed. Processing the input dynamic images in real time requires high performance hardware as well as efficient software. The proposed moving window scheme relieves the requirements for detecting lanes and obstacles from the images in real time. The size of the moving window is optimally determined based upon road and automobile conditions to be big enough to detect the lanes and obstacles and to be small enough to process the detection procedure in real time. For each image frame, the moving window is newly defined and it is moved in a certain direction that is predicted by the Kalman filtering technique. By detecting the left and right lane marks of the driving lane, it becomes possible to search for obstacles within the lane. The obstacle can be verified through the correlation between the stochastic characteristics of the suspected obstacle and the actual obstacle in the database. The feasibility of the proposed algorithm is demonstrated through the simulated experiments of freeway driving.

This paper presents how the control performance of the feature-based visual servo system is improved by utilizing redundant features. The effectiveness of the redundant features is evaluated by the smallest singular value of the image Jacobian which is closely related to the accuracy in the world coordinate system. Usefulness of the redundant features is verified by the real time experiments. To investigate the accuracy of the redundant visual servo control, real time experiments on the dual-arm robot with eight joints are carried out. The rotation and translation step responses with three, four and five features are examined.

In this paper, the localization of a mobile robot using images of a moving target is introduced. Typical objects are stored in the database for the localization of the mobile robot. With a fixed camera, a perspective camera model and a given object database, an image frame can provide the pose (distance and orientation) of the object with respect to the camera. Utilizing the consecutive image frames and motion estimation technology, the relative pose of the object with respect to the camera can be obtained accurately; and during the process, calibration of camera with respect to the world frame, i.e. localization of a mobile robot, is gradually performed. This localization scheme is demonstrated by the experiments.

Introduces a methodology of recognizing the position of a mobile/task robot using an active calibration method. The major problem residing in the precise control of a mobile/task robot is providing an accurate and stable base for the task robot through precise control of the mobile robot. The paper proposes a methodology for the precise control of the mobile robot and the active calibration, which recognizes the position of the mobile robot using the camera attached at the hand of the task robot. This method is applied to the manipulation of polygonal and cylindrical objects. This active calibration method is different from the passive calibration, which is performed by using a calibration grid. The active calibration method finds an algorithm to actively compensate camera and robot pose through the correspondence of point, line and conic of an assembly part by using the geometric property during robot operation. Experimental results show that the mobile/task robot improves the task efficiency and compensates actively the pose using the object's model through the active calibration method.

The kinematic control of a redundant arm based on multiple tasks assigned to different locations of the manipulator is presented. This is equivalent to decomposing a redundant arm into two (or more) nonredundant local arms, the basearm and the forearm, at an intermediate arm location or task point called the elbow. A redundant arm is transformed into a serially cooperating dual-arm system, with the cooperation between the local arms being carried out at the elbow. Then, a manipulator end-effector motion specified by a given task is decomposed into motions of individual local arms as well as an end-effector free motion based on achieving maximum efficiency in task execution. To consider global optimization, elbow control is applied to reshaping and reorientation of a manipulability ellipsoid at the end effector during task execution. The resolved rate control of elbow in the end-effector null and free motion space is used to maximize arm homogeneity and to match the forearm motion space with the task space. Simulation results are shown.>