In the steel industry, the detection of tiny defects including its 3D characteristics on steel surfaces is very important from the point of view of quality control. A multi-spectral photometric stereo method is an attractive scheme because the shape of the defect can be obtained based on the images which are acquired at the same time by using a multi-channel camera. Moreover, the calculation time required for this scheme can be greatly reduced for real-time application with the aid of a GPU (Graphic Processing Unit). Although a more reliable shape reconstruction of defects can be possible when the numbers of available images are increased, it is not an easy task to construct a camera system which has more than 3 channels in the visible light range. In this paper, a new 6-channel camera system, which can distinguish the vertical/horizontal linearly polarized lights of RGB light sources, was developed by adopting two 3-CCD cameras and two polarized lenses based on the fact that the polarized light is preserved on the steel surface. The photometric stereo scheme with 6 images was accelerated by using a GPU, and the performance of the proposed system was validated through experiments.

A 3D visual sensing method using a laser structured beam is presented for robotic tracking applications in a simple and reliable manner. A cylindrical shaped laser structured beam is proposed to measure the pose and position of the target surface. When the proposed laser beam intersects on the surface along the target trajectory, an elliptic pattern is generated. Its ellipse parameters can be induced mathematically by the geometrical relationship of the sensor coordinate and target coordinate. The depth and orientation of the target surface are directly determined by the ellipse parameters. In particular, two discontinuous points on the ellipse pattern, induced by seam trajectory, indicate mathematically the 3D direction for robotic tracking. To investigate the performance of this method, experiments with a 6 axis robot system are conducted on two different types of seam trajectories. The results show that this method is very suitable for robot seam tracking applications due to its excellence in accuracy and efficiency.

In a the present day, many vision inspection techniques are used in productive industrial areas. In particular, in the semiconductor industry the vision inspection system for wafers is a very important system. Also, inspection techniques for semiconductor wafer production are required to ensure high precision and fast inspection. In order to achieve these objectives, parallel processing of the inspection algorithm is essentially needed. In this paper, we propose the GPU (Graphical Processing Unit)-based parallel processing algorithm for the fast inspection of semiconductor wafers. The proposed algorithm is implemented on GPU boards made by NVIDIA Company. The defect detection performance of the proposed algorithm implemented on the GPU is the same as if by a single CPU, but the execution time of the proposed method is about 210 times faster than the one with a single CPU.

Hyperspectral cameras acquire reflectance values at many different wavelength bands. Dimensions tend to increase because spectral information is stored in each pixel. Several attempts have been made to reduce dimensional problems such as the feature selection using Adaboost and dimension reduction using the Simulated Annealing technique. We propose a novel material detection method that consists of four steps: feature band selection, feature extraction, SVM (Support Vector Machine) learning, and target and specific region detection. It is a combination of the band ratio method and Simulated Annealing algorithm based on detection rate. The experimental results validate the effectiveness of the proposed feature selection and band ratio method.

Depth extraction using the structured illumination method is popularly applied since it has the benefit of measuring the object without contact. With multiple spatial frequencies and phase-shifting techniques, it is possible to extract the depth of objects with large discontinuity. For applications such as 3D (Three Dimensional) displays, 3D information of the object is required and is useful if corresponding to each view of the display. For this purpose, hypercentric optics is appropriate to measure the depth information of an object with a large field of view that is applicable for a 3D display. By experiment, we present the feasibility for phase-shifting profilometry using hypercentric optics to obtain the depth information of an object with the field of view appropriate for a 3D display.

AVI (Automatic Vision Inspection) systems automatically detect defect features and measure their sizes via camera vision. Defect detection is not an easy process because of noises from various sources and optical distortion. In this paper the acquired images from a TFT panel are enhanced with the adoption of an HVS (Human Visual System). A human visual system is more sensitive on the defect area than the illumination components because it has greater sensitivity to variations of intensity. In this paper we modified an MTF (Modulation Transfer Function) in the Wavelet domain and utilized the characteristics of an HVS. The proposed algorithm flattens the inner illumination components while preserving the defect information intact.

This paper presents a learning-based visual inspection method that addresses the need for an improved adaptability of a visual inspection system for parts verification in panorama sunroof assembly lines. It is essential to ensure that the many parts required (bolts and nuts, etc.) are properly installed in the PLC sunroof manufacturing process. Instead of human inspectors, a visual inspection system can automatically perform parts verification tasks to assure that parts are properly installed while rejecting any that are improperly assembled. The proposed visual inspection method is able to adapt to changing inspection tasks and environmental conditions through an efficient learning process. The proposed system consists of two major modules: learning mode and test mode. The SVM (Support Vector Machine) learning algorithm is employed to implement part learning and verification. The proposed method is very robust for changing environmental conditions, and various experimental results show the effectiveness of the proposed method.

In this paper, a robot arm capable of recognizing and drawing various line thicknesses is developed. Conventional line drawing robots are not capable of adjusting the thickness of lines. However, to draw faster and to enrich the expression of line drawing robots, it is necessary to adjust line thickness using a brush pen. Simple images are acquired and various line thicknesses are recognized by image processing. Trajectories of lines are generated with distance sorting using thinning and corner point detections for each label. Information on line thickness and trajectory is sent to the controller of a robot arm taking into consideration 2D inverse kinematics. Through this process, the robot arm can draw various lines thicknesses along 2D trajectories with 3 motors. Robot arm for detailed drawing will be studied in the future.

In this paper, the disturbance applied to launcher hatch by ship motions is introduced to identify the vertical ship motion disturbance. Basically, ship motions are comprised of 6 degrees of freedom: roll, pitch, yaw, heave, surge and sway. In the case of the shipboard launcher hatch the coupled pitch, heave and roll are significant motions to be transformed to a vertical direction motion. The maximum acceleration values are obtained from the vertical motion model and the ship motion data in accordance with ship type and hatch location on the ship. We verify that the maximum pitch motion mainly influences the launcher hatch and also present the quantity of the maximum load disturbance by the ship's motion acceleration.

In this paper we propose a novel torque control method for permanent magnet synchronous motors using the SVPWM (Space Vector PWM). The control law is described in the rotating d-q frame and is devised to track a given reference flux with which the reference torque is generated. The key feature of the proposed control is that it provides uniform dynamics with desired closedloop poles independent of the rotating speed and the desired poles can be selected to yield a fast response with only a small amount of torque ripple.

Nowadays, embedded software development using the MATLAB/Simulink system is gradually emerging. Studies generating the parts of embedded S/W in a Rapid Prototype are presented. In this paper, a method to generate the entire embedded S/W of enhanced AC motor control is proposed. High performance motor control could not be achieved with the basic Simulink library and RAppID Toolbox library as it does not have PWM based Interrupt, an ASAC (Analog Sensing for AC Motors) function and other special functions of the Freescale MPC555x. Consequently, the required libraries for enhanced AC motor control are created by Legacy code tool, TLC (Target Language Compiler) and S-Function (System-Function) of MATLAB/ Simulink and utilized in the Rapid Prototype. Motor control performance and execution time are compared automatically to the generated-code S/W with the hand coded S/W. The IPMSM (Interior Permanent Magnet Synchronous Motor) and MPC5553 board that were designed as the AC motor controller for hybrid electrical vehicle are used for the test. The performances meet the requirements and satisfactory results are acquired.

In swarm robot systems, it is vital to maintain network connectivity to ensure cooperative behavior between robots. This paper deals with the behavior control algorithm of the swarm robots for maintaining network connectivity. To do this, we divide swarm robots into search-robots, base-robots, and relay-robots. Using these robots, we propose behavior control algorithm to maintain network connectivity. The behavior control algorithms to maintain network connectivity are proposed for the local path planning using virtual force and global path planning using the Delaunay triangulation, respectively. Finally, we demonstrate the effectiveness and applicability of the proposed method through some simulations.

This paper proposes a tactile transfer and display method between a data glove and vibration motors module. The data glove is developed to capture the hand postures and to measure the grip forces. The measured data are simplified with the proposed 5-bit transfer and display algorithm, and the vibration motors module is developed to display the measured hand posture and grip force to the operator. The proposed 5-bit algorithm contains both an 8-step hand posture and 4-step grip force level information for tactile transfer to the vibration motors module. Also, the effectiveness of the proposed method is shown through several experiments.

Kinematic modeling is a prerequisite for motion planning and the control of mobile robots. In this paper, we proposed a new method of kinematic modeling for a type of mobile robot based on differential motion transformation. The differential motion implies a small translation and rotation in three-dimensional space in a small time interval. Thus, transformation of the differential motion gives the velocity relationship, i.e., Jacobian between two coordinate frames. Since the theory of the differential motion transformation is well-developed, it is useful for the systematic velocity kinematic modeling of mobile robots. In order to show the validity for application of the differential motion transformation, we obtained velocity kinematic models for a type of exemplar mobile robot including spherical ballbots.

This paper proposes an effective walking system for a hexapod robot on uneven terrain. To overcome the deficiencies of two-pair walking systems, which are effective on even terrain, the use of only three legs changes the steps required for movement. The proposed system receives feedback data from switches attached to the bottom of the legs and gyro sensor to carry out stable walking using the Bezier curve algorithm. From the coordinates of the Bezier curve, which guarantees the circular motion of legs, the motor's angle value can be obtained using inverse kinematics. The angle values are sent to each motor though RS-485 communication. If a switch is pushed by the surface during navigation in the Bezier curve pattern, the robot is designed to change its circular course. Through the changed course, each leg can be located on an optimal surface and the wobble phenomenon is reduced by using a normal vector algorithm. The simulation and experiment results show the efficiency of the proposed algorithm.

This paper presents feedforward controllers to improve the control performance of the motion and grasping force of a surgical instrument used in an MIS (Minimally Invasive Surgery) robot. The surgical instrument has a long distance between the drive motors and its active joints. Therefore, the gripper on the instrument is controlled by a cable drive mechanism, which generates a coupled motion between the wrist joint and the grip direction. In order to solve the problem, this paper analyzes the pulley composition of the surgical instrument and proposes feedforward controllers to eliminate the coupled motion. Furthermore, feedforward controllers to regulate the grasping force are proposed to deal with another coupling problem between the grasping force of the instrument and the motion of the instrument joints. The experimental results demonstrate the improved control performance of the motion and grasping force of the instrument.