This paper presents the motion planning of robotic vehicles for the path tracking and the obstacle avoidance. To follow the given path, the vehicle moves through the turning radius obtained through the pure pursuit method, which is a geometric path tracking method. In this paper, we assume that the vehicle is equipped with a 2D laser scanner, allowing it to avoid obstacles within its sensing range. The turning radius for avoiding the obstacle, which is inversely proportional to the virtual force, is then calculated. Therefore, these two kinds of the turning radius are used to generate the steering angle for the front wheel of the vehicle. And the vehicle reduces the velocity when it meets the obstacle or the large steering angle using the potentials of obstacle points and the steering angle. Thus the motion planning of the vehicle is done by planning the steering angle for the front wheels and the velocity. Finally, the performance of the proposed method is tested through simulation.

Lane marking detection is one of important issues in the field of autonomous mobile robot. Especially, in urban environment, like pavement roads of downtown or tour tracks of Science Park, which have continuous patterns on the surface of the road, the lane marking detection becomes more important ability. Although there were many researches about lane detection and lane tracing, many of them used vision sensors mainly to detect lane marking. In this paper, we obtain 2 dimensional library data of 'Intensity' and 'Distance' using one laser rangefinder only. We design a simple classifier and filtering algorithm for the lane detection which uses only one LRF (Laser Range Finder). Allowing extended usage of LRF, this research provides more functionality not only in range finding but also in lane detecting to mobile robots. This work will be technically helpful for robot developers to design more simple and efficient autonomous driving system using LRF.

This paper presents a new fuzzy model-based design approach for waypoints-tracking control of nonlinear underwater vehicles (UUVs) on a horizontal plane. The waypoints-tracking control problem is converted into the stabilization one for the error model between the given nonlinear UUV and the waypoints. By using the sector nonlinearity, the error model is modeled in Takagi-Sugeno's form. We then derive stabilization conditions for the error model in the format of linear matrix inequality. A numerical simulation is provided to illustrate the effectiveness of the proposed methodology.

This paper describes a novel sensor system for 3D world modeling of an autonomous vehicle in large-scale outdoor environments. When an autonomous vehicle performs path planning and path following, well-constructed 3D world model of target environment is very important for analyze the environment and track the determined path. To generate well-construct 3D world model, we develop a novel sensor system. The proposed novel sensor system consists of two 2D laser scanners, two single cameras, a DGPS (Differential Global Positioning System) and an IMU (Inertial Measurement System). We verify the effectiveness of the proposed sensor system through experiment in large-scale outdoor environment.

This paper describes an intelligent service robot system for managing a store in an unmanned environment. The robot can be a good replacement for humans because it is possible to work all day and to remember lots of information. We design a system architecture for configuring many intelligent functions of intelligent service robot system which consists of four layers; a User Interaction Layer, a Behavior Scheduling Layer, a Intelligent Module Layer, and a Hardware Layer. We develop an intelligent service robot 'Part Timer' based on the designed system architecture. The 'Part Timer' has many intelligent function modules such as face detection-recognition-tracking module, speech recognition module, navigation module, manipulator module, appliance control module, etc. The 'Part Timer' is possible to answer the phone and this function gives convenient interface to users.

Tilt sensor is required to control the attitude of the biped robot when it walks on an uneven terrain. Vision sensor, which is used for recognizing human or detecting obstacles, can be used as a tilt angle sensor by comparing current image and reference image. However, vision sensor alone has a lot of technological limitations to control biped robot such as low sampling frequency and estimation time delay. In order to verify limitations of vision sensor, experimental setup of an inverted pendulum, which represents pitch motion of the walking or running robot, is used and it is proved that only vision sensor cannot control an inverted pendulum mainly because of the time delay. In this paper, to overcome limitations of vision sensor, Kalman filter for the multi-rate sensor fusion algorithm is applied with low-quality gyro sensor. It solves limitations of the vision sensor as well as eliminates drift of gyro sensor. Through the experiment of an inverted pendulum control, it is found that the tilt estimation performance of fusion sensor is greatly improved enough to control the attitude of an inverted pendulum.

This paper presents experimental results on the energy-bounding approach to a rate-mode bilateral teleoperation control that can guarantee the robust system stability in variable time-delayed telecommunication environments. Previously, rate-mode energy bounding approach [15] was proposed and verified with experimental results using the simulated remote slave model. In this paper, a real experimental setup using an industrial robot (Denso) as a remote slave robot composed and conducted similar experiments with previous paper. In order to guarantee stability of the Denso when contacting with high impedance wall, velocity based impedance control modified by position based is used. Experimental results show that the rate-mode energy bounding approach can guarantee stable bilateral teleoperation system in the free and contact motion with variable time delay.

Various robot platforms have been designed and developed to perform given tasks in a hazardous environment for surveillance, reconnaissance, search and rescue, etc. We considered a terrain-adaptive and transformable hybrid robot platform that is equipped with rapid navigation capability on flat floors and good performance in overcoming stairs or obstacles. The navigation mode transition is determined and implemented by adaptive driving mode control of the mobile robot. In order to maximize the usability of wheel-track hybrid robot platform, we propose a terrain-adaptive and user-friendly remote controller and verify the efficiency and performance through its navigation performance experiments in real and test-bed environments.

In recent semiconductor and FPD (Flat Panel Display) manufacturing processes, high clean-class delivery operation is required more and more for short working time and better product quality. Traditionally SLIM (Single-sided Linear Induction Motor) is widely used in the liner drive applications because of its simplicity in the rail structure. A magnetically levitated (Maglev) unmanned vehicle with SLIM traction, which is powered by a CPS (Contactless Power Supply) can be a high precision delivery solution for this industry. In this paper unmanned FPD-carrying vehicle, which can levitate without contacting the rail structure, is suggested for high clean-class FPD delivery applications. It can be more acceptable for the complex facilities composed with many processes which require longer rails, because of simple rail structure. The test setup consists of a test vehicle and a rounded rail, in which the vehicle can load and unload products at arbitrary position commanded through wireless communications of host computer. The experimental results show that the suggested vehicle and rail have reasonable traction servo and robust electromagnetic suspensions without any contact. The resolution of point servo errors in the SLIM traction system is accomplished under 1mm. The maximum gap error is ${\pm}0.25mm$ with nominal air gap length of 4.0mm in the electromagnetic suspensions. This type of automated delivery vehicle is expected to have significant role in the clean delivery like FPD glass delivery.

We propose a switching-based adaptive state feedback controller for a class of nonlinear systems that have uncertain nonlinearity. The base of the proposed conditions on the nonlinearity is the feedforward form, then it is extended via a nonlinear function containing all the states and the control input. As a result, more generalized systems containing feedforward and nonfeedforward terms are allowed as long as the ratio condition of the nonlinear function is satisfied. Moreover, the information on the growth rate of nonlinearity is not required a priori in our control scheme.

It is very critical for image processing of IIR (Imaging Infrared) seekers to achieve improved guidance performance for missile systems to determine appropriate thresholds in various environments. In this paper, we propose automatic threshold determination methods for proper thresholds to extract definite target signals in an EOCM (Electro-Optical Countermeasures) environment with low SNR (Signal-to-Noise Ratios). In particular, thresholds are found to be too low to extract target signals if one uses the Otsu method so that we suggest a Shifted Otsu method to solve this problem. Also we improve extracting target signal by changing Shifted Otsu thresholds according to the TBR (Target to Background Ratio). The suggested method is tested for real IIR images and the results are compared with the Otsu method. The HPDAF (Highest Probabilistic Data Association Filter) which selects the target originated measurements by taking into account of both signal intensity and statistical distance information is applied in this study.

In this paper, we focus on the issue of automatic selection for multi-level threshold, and we greatly improve the efficiency of Otsu's method for image segmentation based on genetic algorithm. We have investigated and evaluated the performance of the Otsu and Valley-emphasis threshold methods. Based on this observation we propose a method for automatic threshold method that segments an image into more than two regions with high performance and processing in real-time. Our paper introduced new peak detection, combines with evolution algorithm using MAGA (Modified Adaptive Genetic Algorithm) and HCA (Hill Climbing Algorithm), to find the best threshold automatically, accurately, and quickly. The experimental results show that the proposed evolutionary algorithm achieves a satisfactory segmentation effect and that the processing time can be greatly reduced when the number of thresholds increases.

Autonomous navigating algorithms for mobile robots have been proved to be a difficult task. Based on the excellent homing performance shown by many insects, bio-inspired navigation algorithms for robotic experiments have been widely researched and applied to the design of navigational strategies for mobile robots. In this paper, among them, we analyze two simple landmark navigation methods their strengths and limits. We investigate the effect of the occlusion problem mainly, which is an important yet tough problem in many landmark navigation algorithms. In the point of view of the error of homing vector and the performance of the homing paths in the environment with artificial occlusions, we investigate the effect of occlusion problem in both methods in order to further study on solutions.

In this paper, we standardized the water operation system picture, process control logic, realtime database and system configuration. All aspects, including monitoring & controlling processes, symbols such as pumps, valves and pipes were standardized. As a result we have developed a specialized Integrated water operation system, iWater. We have developed a variety of advanced application programs that are essential for water treatment systems, such as IWS (Integrated Warning system), MBO(modbus opc)/LSE(LS ethernet) driver, video monitoring, self diagnosis system, network monitoring, etc. IWS prevents water supply accidents by using a variety of alarms and warning messages. Drivers have the flexibility to communicate with other 3rd party systems. We expect that iWater will eliminate any concerns regarding water-related issues while also promoting the production and fair distribution of clean water.

For improved localization around the indoor/outdoor transit area of buildings, this paper proposes an efficient algorithm combining the measurements from the WLAN (Wireless Local Area Network) and the GPS (Global Positioning System) for. The proposed hybrid localization algorithm considers both multipath errors and NLOS (Non-Line-of-Sight) errors, which occur in most wireless localization systems. To detect and isolate multipath errors occurring in GPS measurements, the propose algorithm utilizes conventional multipath test statistics. To convert WLAN signal strength measurements to range estimates in the presence of NLOS errors, a simple and effective calibration algorithm is designed to compute conversion parameters. By selecting and combining the reliable GPS and WLAN measurements, the proposed hybrid localization algorithm provides more accurate location estimates. An experiment result demonstrates the performance of the proposed algorithm.