This paper presents some real performance of two typical bilateral teleoperation benchmark tasks: peg-in-hole and surface tracking tasks. The tasks are performed by an energy-bounding algorithm in the master control and position-based impedance algorithm in the slave control. Performance is analyzed for the position-force tracking capabilities from free space motion to surface contacting motion. In addition, preliminary user performance is evaluated by measuring the completion time and maximum/average contact forces. The quality of the measured performance is also compared with that of other existing approaches.

In this paper, a vibrotactile pad system, T-mobile, is developed to provide vibrotactile cues for hand-held devices. A grooved and slim design is adapted to the back-side plane of the T-mobile, and the contact part consists of 12 vibrotactile panels which can operate independently and separately. To be isolated among vibrotactile actuators, the surface of the cover is divided into several pieces. Each vibrating module consists of a linear resonant actuator, a section of covering surface, and a vibration isolator. In order to provide spatial and directional information, sensory saltation and phantom sensation are applied to the T-mobile. To evaluate the developed device, two experiments were conducted to test whether directional information and spatial information can be successfully displayed by the device. Additionally, in order to find optimal stimulation by sensory saltation, an empirical test was conducted. As a result, spatial and directional information would be useful for displaying intuitive information for hand-held devices with vibrotactile feedback and reasonable near-optimal value for sensory saltation was obtained.

LAS (Laparoscopy Assisted Surgery) has been substituted alternatively for traditional open surgery. However, when using a commercialized robot assisted laparoscopic such as Da Vinci, surgeons have encountered some problems due to having to depend only on information by visual feedback. To solve this problem, a haptic function is required. In order to realize the haptic teleoperation system, a force feedback and bilateral control system are needed. Previous research showed that the perturbation value estimated by a SPO (Sliding Perturbation Observer) followed a reaction force that loaded on the surgical robot instrument. Thus, in this paper, the force feedback problem of surgical robots is solved through the reaction force estimation method. This paper then introduces the possibility of the haptic function realization of a laparoscopic surgery robot using a bilateral control system. For bilateral control, the master uses an impedance control and the slave uses a SMC (Sliding Mode Control). The experiment results show that a torque and force sensorless teleoperation system can be implemented using a bilateral control structure.

In this paper, we proposed a haptic navigation system which used the tactile data for the user guides of the mobile robot to the reference point via tele-operation in unknown blind environment. This navigation system can enable a mobile robot to avoid obstacles and move to the reference point, according to the direction provided by the device guides through a haptic device consisting of a vibration motor in a blind environment. There are a great deal of obstacles in real environments, and so mobile robots can avoid obstacles by recognizing the exact position of each obstacle through the superposition of an ultrasonic sensor. The navigation system determines the direction of obstacle avoidance through an avoidance algorithm that uses virtual impedance, and lets users know the position of obstacles and the direction of the avoidance through the haptic device consisting of 5 vibration motors. By letting users know intuitionally, it lets the mobile robot precisely reach the reference point in unknown blind environment. This haptic device can implement a haptic navigation system through the tactile sensor data.

In this paper, we propose a novel CALL (Computer-Assisted Language Learning) system, which is called POMY (POSTECH Immersive English Study). In our system, students can study English while talking to characters in a computer-generated virtual environment. POMY also supports haptic feedback, so students can study English in a more interesting manner. Haptic feedback is provided by two platforms, a haptic chair and a force-feedback device. The haptic chair, which is equipped with an array of vibrotactile actuators, delivers directional information to the student. The force-feedback device enables the student to feel the physical properties of an object. These haptic systems help the student better understand English conversations and focus on studying. We conducted a user experiment and its results showed that our haptic-enabled English study contributes to better learning of English.

This paper presents a robust observer-based output feedback control for stabilization of linear time invariant systems with polytopic uncertainties. To this end, this paper not only finds a robust observer gain but also suggests how to determine the model used in the observer, which is not obvious due to model uncertainties in the conventional observer design method. The robust observer gain and the observer model are selected in a way that the whole closed-loop is stable by solving LMIs and BMIs (Linear Matrix Inequalities and Bilinear Matrix Inequalities). A simulation example shows that the proposed robust observer-based output feedback control successfully leads to closed-loop stability.

This paper presents a comparison among three types of approaches to an ARC (Active Roll Control) with an AARB(Active Anti-Roll Bar) for a vehicle system. Lateral acceleration and road profile are considered as disturbance. The ARC is designed with an LQ SOF (Linear Quadratic Static Output Feedback) control, $H_{\infty}$ control and SMC (Sliding Mode Control). These approaches are compared in terms of rollover prevention and ride comfort. For comparison, Bode plot analysis based on linear model and frequency response analysis based on CarSim simulation are performed.

In this paper we propose a swing-up strategy for a single inverted pendulum. The proposed method has a feature whereby can handle the input and output constraint of a pendulum in a systematic way. For the swing-up of a pendulum, we adopt a 2-DOF control structure that combines the feedforward and feedback control. In order to generate the swing-up feedforward trajectories that satisfy the input and output constraint, we formulate the problem of generating feedforward trajectories as a nonlinear optimal control problem subject to constraints. We illustrate that the proposed method is more flexible than the existing method and provides great freedom in choosing the actuator of the inverted pendulum. Through an experiment, we show that the proposed method can swing a pendulum upward effectively while satisfying all the imposed constraints.

In this paper, an improved method RMBE (Resizable Model Based target size Estimator) is presented for SDIIR (Strap Down Imaging Infrared) seekers. At the target engaging scenario, the IIR target measurement is separated by various parts. In this case, target object changing is important to accurate target intercept. Therefore, we need robust target size estimator. Our proposed method resize estimated target size with MC-1 (Markov Chain I) for accurate target size estimation. The performance of proposed method is tested at IIR target tracking of target intercept scenario. The experiment results show that the proposed RMBE has improved performance than MBE.

In micro-scale electromechanical systems, the power to perform accurate position sensing often greatly exceeds the power needed to generate motion. This paper explores the implications of sampling rate and amplifier noise density selection on the performance of a system identification algorithm using a capacitive sensing circuit. Specific performance objectives are to minimize or limit convergence rate and power consumption to identify the dynamics of a rotary micro-stage. A rearrangement of the conventional recursive least-squares identification algorithm is performed to make operating cost an explicit function of sensor design parameters. It is observed that there is a strong dependence of convergence rate and error on the sampling rate, while energy dependence is driven by error that may be tolerated in the final identified parameters.

This paper deals with the performance comparison of a PSO algorithm inspired in the process of simulating the behavior pattern of the organisms. The PSO algorithm finds the optimal solution (fitness value) of the objective function based on a stochastic process. Generally, the stochastic process, a random function, is used with the expression related to the velocity included in the PSO algorithm. In this case, the random function of the normal distribution (Gaussian) or uniform distribution are mainly used as the random function in a PSO algorithm. However, in this paper, because the probability distribution which is various with 2 shape parameters can be expressed, the performance comparison of a PSO algorithm using the beta probability distribution function, that is a random function which has a high degree of freedom, is introduced. For performance comparison, 3 functions (Rastrigin, Rosenbrock, Schwefel) were selected among the benchmark Set. And the convergence property was compared and analyzed using PSO-FIW to find the optimal solution.

This paper proposes a novel mapping algorithm in Omni-directional Vision SLAM based on an obstacle's feature extraction using Lucas-Kanade Optical Flow motion detection and images obtained through fish-eye lenses mounted on robots. Omni-directional image sensors have distortion problems because they use a fish-eye lens or mirror, but it is possible in real time image processing for mobile robots because it measured all information around the robot at one time. In previous Omni-Directional Vision SLAM research, feature points in corrected fisheye images were used but the proposed algorithm corrected only the feature point of the obstacle. We obtained faster processing than previous systems through this process. The core of the proposed algorithm may be summarized as follows: First, we capture instantaneous $360^{\circ}$ panoramic images around a robot through fish-eye lenses which are mounted in the bottom direction. Second, we remove the feature points of the floor surface using a histogram filter, and label the candidates of the obstacle extracted. Third, we estimate the location of obstacles based on motion vectors using LKOF. Finally, it estimates the robot position using an Extended Kalman Filter based on the obstacle position obtained by LKOF and creates a map. We will confirm the reliability of the mapping algorithm using motion estimation based on fisheye images through the comparison between maps obtained using the proposed algorithm and real maps.

The redundancy resolution of the seven DOF (Degree of Freedom) upper limb exoskeleton is key to the synchronous motion between a robot and a human user. According to the seven DOF human arm model, positioning and orientating the wrist can be completed by multiple arm configurations that results in the non-unique solution to the inverse kinematics. This paper presents analysis on the kinematic and dynamic aspect of the human arm movement and its effect on the redundancy resolution of the seven DOF human arm model. The redundancy of the arm is expressed mathematically by defining the swivel angle. The final form of swivel angle can be represented as a linear combination of two different swivel angles achieved by optimizing two cost functions based on kinematic and dynamic criteria. The kinematic criterion is to maximize the projection of the longest principal axis of the manipulability ellipsoid of the human arm on the vector connecting the wrist and the virtual target on the head region. The dynamic criterion is to minimize the mechanical work done in the joint space for each of two consecutive points along the task space trajectory. The contribution of each criterion on the redundancy was verified by the post processing of experimental data collected with a motion capture system. Results indicate that the bimodal redundancy resolution approach improved the accuracy of the predicted swivel angle. Statistical testing of the dynamic constraint contribution shows that under moderate speeds and no load, the dynamic component of the human arm is not dominant, and it is enough to resolve the redundancy without dynamic constraint for the realtime application.

This paper deals with a filterbank based on the IMM (Interacting Multiple Model) that combines data from a sensor and uses them selectively depending on a level of maneuver. Furthermore, within the maneuver interval, the existing IMM filter has disadvantages such as unnecessary target estimation errors caused by using a constant velocity model and an increase of computation load because of a fixed structure. On the other hand, the proposed IMM filterbank overcomes these disadvantages by using three model groups and designs a filterbank to cope with a wideband-maneuvering target. The performances of the IMM filterbank was evaluated through comparison with the existing IMM via computer simulations. The results show good performances for a wideband-maneuvering target.

In this paper, we derive the CRLB (Cramer-Rao Lower Bound) of effective carrier-to-noise power ratio ($C/N_0$) estimation for a GPS (Global Positioning System) L1 C/A (Coarse/Acquisition) signal under band-limited white noise jamming environments. The quality of a received GPS signal is commonly described in terms of its $C/N_0$, implying that the noise is white and thus can be described by scalar noise density. However, if some intentional interference is received to a victim GPS receiver, then the $C/N_0$ is no longer the efficacious performance indicator. The correct and straightforward measurement to analyze the receiving situation is the effective $C/N_0$. In this paper, we consider a band-limited white noise jamming whose bandwidth is 2MHz and is the same as one of the first null-to-null bandwidth of the GPS L1 C/A signal.