This paper deals with an anti-sway control for a ship-mounted container crane which is disturbed by the wave-induced motions of the ship. We derive a simple dynamics of the ship-mounted container crane with an active anti-sway control system and transform it into a dynamic function for a horizontal variable on the absolute coordinate. Then we propose an control method to reduce pendulation of the spreader and compare its performance with well-known feedback linearization control in computer simulation.

A new Fuzzy sliding mode controller is proposed to improve the cornering performance of the four wheel hybrid vehicles. The Fuzzy sliding mode control is applied for the control of rear motor and EHB (Electro-Hydraulic Brake) to improve the cornering performance. The modeling of the automobile is simplified that each of the two wheels is modeled as two degrees of freedom object and the friction coefficient between the wheel and the ground is assumed to be constant. The output of the Fuzzy sliding mode algorithm is the direct yaw moment for the rear wheels, which compensates for the slip angle. Through the simulations using ADAMS and MATLAB Simulink, the cornering performance of the proposed algorithm is compared to the conventional PID to show the superiority of the proposed algorithm. In the simulation experiments, the J-Turn and single lane change are used for each of the Fuzzy sliding mode algorithm and PID controller with the optimal gains which are tuned empirically.

To segment instances of vehicle classes in a sparse stereo-matching data set, this paper presents an algorithm for clustering based on DP (Dynamic Programming). The algorithm is agglomerative: it begins with each element in the set as a separate cluster and merges them into successively larger clusters according to similarity of two clusters. Here, similarity is formulated as a cost function of DP. The proposed algorithm is proven to be effective by experiments performed on various images acquired by a moving vehicle.

In this paper, we proposed an omnidirectional ranging system that is able to obtain $360^{\circ}$ all directional distances effectively based on structured light image. The omnidirectional ranging system consists of laser structured light source and a catadioptric omnidirectional camera with a curved mirror. The proposed integro-differential structured light image processing algorithm makes the ranging system robust against environmental illumination condition. The omnidirectional ranging system is useful for map-building and self-localization of a mobile robot.

In this paper, a new method to recognize various motions of fighting with an aid of HMM is proposed. There are four kinds of fighting motion such as hook, jab, uppercut, and straight as the fighting motion. The motion graph is generalized to define each motion in motion data and the new 3D-chain code is used to convert motion data to motion graphs. The recognition experiment has been performed with HMM algorithm on motion graphs. The motion data is captured by a motion capture system developed in this study and by five actors. Experimental results are given with relatively high recognition rate of at least 85%.

This paper presents the design of optimal fuzzy classifier for human detection by using genetic algorithms, one of the best-known meta-heuristic search methods. For this purpose, encoding scheme to search the optimal sequential intersection points between adjacent fuzzy membership functions is originally presented for the fuzzy classifier design for HOG (Histograms of Oriented Gradient) descriptors. The intersection points are sequentially encoded in the proposed encoding scheme to reduce the redundancy of search space occurred in the combinational problem. Furthermore, the fitness function is modified with the true-positive and true-negative of the confusion matrix instead of the total success rate. Experimental results show that the two proposed approaches give superior performance in HOG datasets.

In this paper, we present an effective covariance tracking algorithm based on adaptive size changing of tracking window. Recent researches have advocated the use of a covariance matrix of object image features for tracking objects instead of the conventional histogram object models used in popular algorithms. But, according to the general covariance tracking algorithm, it can not deal with the scale changes of the moving objects. The scale of the moving object often changes in various tracking environment and the tracking window(or object kernel) has to be adapted accordingly. In addition, the covariance matrix of moving objects should be adaptively updated considering of the tracking window size. We provide a solution to this problem by segmenting the moving object from the background pixels of the tracking window. Therefore, we can improve the tracking performance of the covariance tracking method. Our several simulations prove the effectiveness of the proposed method.

This paper presents a method that integrates the geometric path tracking and the obstacle avoidance for nonholonomic mobile robot. The mobile robot follows the path by moving through the turning radius given from the pure pursuit method which is the one of the geometric path tracking methods. And the obstacle generates the obstacle potential, from this potential, the virtual force is obtained. Therefore, the turning radius for avoiding the obstacle is calculated by proportional to the virtual force. By integrating the turning radius for avoiding the obstacle and the turning radius for following the path, the mobile robot follows the path and avoids the obstacle simultaneously. The effectiveness of the proposed method is verified through the real experiments for path tracking only, static obstacle avoidance, dynamic obstacle avoidance.

The OPRoS (Open Platform for Robotic Services) framework is proposed as an application runtime environment for service robot systems. For the successful deployment of the OPRoS framework, fault tolerance support is crucial on top of its basic functionalities of lifecycle, thread and connection management. In the previous work [1] on OPRoS fault tolerance supports, we presented a framework-based fault tolerance architecture. In this paper, we extend the architecture with component-based fault tolerance techniques, which can provide more simplicity and efficiency than the pure framework-based approach. This argument is especially true for fault detection, since most faults and failure can be defined when the system cannot meet the requirement of the application functions. Specifically, the paper applies two widely-used fault detection techniques to the OPRoS framework: 'bridge component' and 'process model' component techniques for fault detection. The application details and performance of the proposed techniques are demonstrated by the same application scenario in [1]. The combination of component-based techniques with the framework-based architecture would improve the reliability of robot systems using the OPRoS framework.

This paper proposes a new method called the path-history coverage to generate a test suite to test the state transition behavior of the robot SW component. The proposed method generate a test suite which includes abnormal state transitions based on FSM of target component. Especially the proposed method covers the disadvantage of the mutation test method that the size of the test suite is explosively increasing. Examples including OPRoS Component[1] show the validity of the proposed method.

This paper presents a new obstacle-avoidance method for mobile robots. This approach, called the FEB (Fast Elastic Band) method, has been developed and successfully tested on the experimental mobile robot PHOPE-1S. The FEB method eliminates the shortcomings of the elastic band method previously introduced, yet retains all the advantages of its predecessor. The FEB algorithm is computationally efficient, and it allows continuous and fast motion of the mobile robot without stopping for obstacles. The FEB-controlled mobile robot traverses very densely cluttered obstacle courses and is able to pass through narrow openings or narrow corridors without oscillations. The results of the simulation and experiment have verified the validity of the proposed method.

Recently, there is a rising interest on studying bio-inspired robotic fish because of real fish's great maneuverability and high energy efficiency. However, the researches about the robotic fish have not been done so much and there are still lots of problems to use them in the real environment such as in the river. This paper describes a bio-inspired robotic fish 'Ichthus' which is developed in KITECH and has 3 DOF propulsive mechanism. We develop the dynamic motion equation of 'Ichthus' in the underwater environment and analyze response characteristics of 'Ichthus' according to the input parameters of tail fin's amplitude and oscillation frequency. Then we propose control parameters at the various velocities. These parameters are useful to increase energy efficiency and it can be used when the fish robot moves in the real environment, for example, we can propose proper amplitude and oscillation frequency when the fish robot passes through the narrow space between obstacles.

This paper proposes a Taylor-series design method which reduces the height error of the tag when readers are arranged at the same height in 3-dimensional space. The proposed method consists of two steps. Firstly, the planar position is estimated by the Taylor-series method using the TDOA measurement. Next, the height is estimated from the estimated planar position. In order to show the validity of the proposed method, computer simulations were performed for the static case and linear trajectory of the tag. Results show that the proposed method gives convergent estimated position and better height estimate than the Taylor series method.

This paper proposes a vision/DR integrated navigation system using distance between wheels of the vehicle and a gyroscope. In order to show the validity of the proposed vision/DR integrated navigation system, experiments were performed for a trajectory of a mobile robot. Experimental results show that the proposed vision/DR integrated navigation system gives better navigation performance than a vision/DR integrated navigation system using only distance between wheels of the vehicle.

In this paper, we propose an algorithm to improve TCP performance over wireless links. TCP is known to have poor performance over wireless links because TCP has no mechanism to differentiate congestion loss from wireless loss, and treats all losses as congestive. We present a simple method to determine the cause of packet loss using the successive ECN. In addition, we present an algorithm to control the congestion window size based on the estimated queue state in order to guarantee the fairness and high link utilization.