Showing papers in "Journal of Institute of Control Robotics and Systems in 2011"

Motion and Force Estimation System of Human Fingers

Abstract: This presents a motion and force estimation system of human fingers by using an Electromyography (EMG) sensor module and a data glove system to be proposed in this paper. Both EMG sensor module and data glove system are developed in such a way to minimize the number of hardware filters in acquiring the signals as well as to reduce their sizes for the wearable. Since the onset of EMG precedes the onset of actual finger movement by dozens to hundreds milliseconds, we show that it is possible to predict the pattern of finger movement before actual movement by using the suggested system. Also, we are to suggest how to estimate the grasping force of hand based on the relationship between RMS taken EMG signal and the applied load. Finally we show the effectiveness of the suggested estimation system through several experiments.

Resilience Allocation for Resilient Engineered System Design

Abstract: Most engineered systems are designed with high levels of system redundancies to satisfy required reliability requirements under adverse events, resulting in high systems’ LCCs (Life-Cycle Costs). Recent years have seen a surge of interest and tremendous advance in PHM (Prognostics and Health Management) methods that detect, diagnose, and predict the effects of adverse events. The PHM methods enable proactive maintenance decisions, giving rise to adaptive reliability. In this paper, we present a RAP (Resilience Allocation Problem) whose goal is to allocate reliability and PHM efficiency to components in an engineering context. The optimally allocated reliability and PHM efficiency levels serve as the design specifications for the system RBDO (Reliability-Based Design Optimization) and the system PHM design, which can be used to derive the detailed design of components and PHM units. The RAP is demonstrated using a simplified aircraft control actuator design problem resulting in a highly resilient actuator with optimally allocated reliability, PHM efficiency and redundancy for the given parameter settings.

Sdre 기법을 이용한 이륜 밸런싱 로봇의 비선형 최적제어

Abstract: Two-wheeled balancing mobile robots are currently controlled in terms of linear control methods without considering the nonlinear dynamical characteristics. However, in the high maneuvering situations such as fast turn and abrupt start and stop, such neglected terms become dominant and greatly influence the overall driving performance. This paper addresses the SDRE nonlinear optimal control method to take advantage of the exact nonlinear dynamics of the balancing robot. Simulation results indicate that the SDRE control outperforms LQR in the respect of transient performance and required wheel torques. A design example is suggested for the state matrix that provides design flexibility in the SDRE control. It is shown that a well-planned state matrix by reflecting the physics of a balancing robot greatly contributes to the driving performance and stability.

Design of Sliding Mode Controller for Ship Position Control

Abstract: This paper addresses the trajectory tracking problem for ship berthing by using sliding mode technique. With significant potential advantages: insensitivity to plant nonlinearities, parameter variations, remarkable stability and robust performance with environmental disturbances, the multivariable sliding modes controller is proposed for solving trajectory tracking of ship in harbor area. In this study, the ship position and heading angle are simultaneously tracked to guarantees that the ship follows a given path (geometric task) with desired velocities (dynamic task). The stability of the proposed control law is proved based on Lyapunov theory. The proposed approach has been simulated on a computer model of a supply vessel with good results.

Development of precise localization system for autonomous mobile robots using multiple ultrasonic transmitters and receivers in indoor environments

Abstract: A precise embedded ultrasonic localization system is developed for autonomous mobile robots in indoor environments, which is essential for autonomous navigation of mobile robots with various tasks. Although ultrasonic sensors are more cost-effective than other sensors such as LRF (Laser Range Finder) and vision, they suffer inaccuracy and directional ambiguity. First, we apply the matched filter to measure the distance precisely. For resolving the computational complexity of the matched filter for embedded systems, we propose a new matched filter algorithm with fast computation in three points of view. Second, we propose an accurate ultrasonic localization system which consists of three ultrasonic receivers on the mobile robot and two or more transmitters on the ceiling. Last, we add an extended Kalman filter to estimate position and orientation. Various simulations and experimental results show the effectiveness of the proposed system.

An Efficient Outdoor Localization Method Using Multi-Sensor Fusion for Car-Like Robots

Abstract: An efficient outdoor local localization method is suggested using multi-sensor fusion with MU-EKF (Multi-Update Extended Kalman Filter) for car-like mobile robots. In outdoor environments, where mobile robots are used for explorations or military services, accurate localization with multiple sensors is indispensable. In this paper, multi-sensor fusion outdoor local localization algorithm is proposed, which fuses sensor data from LRF (Laser Range Finder), Encoder, and GPS. First, encoder data is used for the prediction stage of MU-EKF. Then the LRF data obtained by scanning the environment is used to extract objects, and estimates the robot position and orientation by mapping with map objects, as the first update stage of MU-EKF. This estimation is finally fused with GPS as the second update stage of MU-EKF. This MU-EKF algorithm can also fuse more than three sensor data efficiently even with different sensor data sampling periods, and ensures high accuracy in localization. The validity of the proposed algorithm is revealed via experiments.

Prm과 포텐셜 필드 기법에 기반한 다자유도 머니퓰레이터의 충돌회피 경로계획

Abstract: The collision-free path of a manipulator should be regenerated in the real time to achieve collision safety when obstacles or humans come into the workspace of the manipulator. A probabilistic roadmap (PRM) method, one of the popular path planning schemes for a manipulator, can find a collision-free path by connecting the start and goal poses through the roadmap constructed by drawing random nodes in the free configuration space. The path planning method based on the configuration space shows robust performance for static environments which can be converted into the off-line processing. However, since this method spends considerable time on converting dynamic obstacles into the configuration space, it is not appropriate for real-time generation of a collision-free path. On the other hand, the method based on the workspace can provide fast response even for dynamic environments because it does not need the conversion into the configuration space. In this paper, we propose an efficient real-time path planning by combining the PRM and the potential field methods to cope with static and dynamic environments. The PRM can generate a collision-free path and the potential field method can determine the configuration of the manipulator. A series of experiments show that the proposed path planning method can provide robust performance for various obstacles.

Monocular Vision and Odometry-Based SLAM Using Position and Orientation of Ceiling Lamps

Abstract: This paper proposes a novel monocular vision-based SLAM (Simultaneous Localization and Mapping) method using both position and orientation information of ceiling lamps. Conventional approaches used corner or line features as landmarks in their SLAM algorithms, but these methods were often unable to achieve stable navigation due to a lack of reliable visual features on the ceiling. Since lamp features are usually placed some distances from each other in indoor environments, they can be robustly detected and used as reliable landmarks. We used both the position and orientation of a lamp feature to accurately estimate the robot pose. Its orientation is obtained by calculating the principal axis from the pixel distribution of the lamp area. Both corner and lamp features are used as landmarks in the EKF (Extended Kalman Filter) to increase the stability of the SLAM process. Experimental results show that the proposed scheme works successfully in various indoor environments.

A Study on Way-Point Tracking of AUV using State Feedback

Abstract: For way-point tracking of an autonomous underwater vehicle, a state feedback controller was designed by using pole placement scheme in discrete time domain. In the controller, 4 state variables were used for regulating the depth of the vehicle in z direction, and 3 state variables, for steering the vehicle in xy plane. Assuming constant speed of AUV, we simplified the design of the way-point tracking system. The proposed controller was simulated by MATLAB/Simulink using 6 degree-of-freedom nonlinear model and its performance of way point tracking was shown to be fulfilled within 1 m, nevertheless the proposed controller is quite simple and easy to implement compared to sliding mode controller.

Development of Magnetic Force Modeling Equipment for Magnetic Levitation Systems

Abstract: This paper proposes an equipment and an algorithm for modeling the magnetic force of electromagnets in magnetic levitation systems. We assume that the magnetic force model is represented in terms of a 2D lookup table. The 2D lookup table is constructed by applying noncausal filtering and interpolation to data measured by the proposed modeling equipment. The proposed modeling equipment is designed such that it can measure the magnetic force exerted on the levitation object while it changes the voltage applied to the electromagnet and position of the levitation object. The algorithm of making a 2D lookup table has two stages. The data measured by the proposed modeling equipment is smoothed by a noncausal filter and then the 2D lookup table is obtained by interpolating filtered data. The proposed modeling method has advantages of time-saving, model consistency, and chance of automation for mass production. We show the validity of proposed method through control experiments.

옴니 카메라의 전방향 영상을 이용한 이동 로봇의 위치 인식 시스템

Abstract: Vision-based robot localization is challenging due to the vast amount of visual information available, requiring extensive storage and processing time. To deal with these challenges, we propose the use of features extracted from omni-directional panoramic images and present a method for localization of a mobile robot equipped with an omni-directional camera. The core of the proposed scheme may be summarized as follows : First, we utilize an omni-directional camera which can capture instantaneous 360˚ panoramic images around a robot. Second, Nodes around the robot are extracted by the correlation doefficients of Circular Horizontal Line between the landmark and the current captured image. Third, the robot position is determined from the locations by the proposed correlation-based landmark image matching. To accelerate computations, we have assigned the node candidates using color information and the correlation values are calculated based on Fast Fourier Transforms. Experiments show that the proposed method is effecitve in global localization of mobile robots and robust to lighting variations.

Development of Agriculture Robot for Unmanned Management in Controlled Agriculture

Abstract: Environmental change, labor shortage, and international trade politics make agricultural automation ever more important. The automation demands the highest technology due to the nature of agriculture. In this paper, autonomous pesticide spray robot system has been developed for rose farming in the glass house. We developed drive platform, navigation/localization system, atomization spray system, autonomous, remote, and manual operation system, and monitoring system. The robot will be a great contribution to automation of hazardous labor-demanding chore of pesticide control in glass houses.

Improved Ultrasonic Satellite System for the Localization of Mobile Robots

Abstract: The localization of mobile robot in environment is a major concern in mobile robot navigation. So, many kinds of localization techniques have been researched for several years. Among them, the positioning system using ultrasound has received attention. Most of these ultrasonic positioning systems to synchronize the transmitters and receivers are used for RF (Radio Frequencies). However, due to the use of RF, the interference problems can not be avoided and the performance of radio frequencies directly affects the positioning performance. So we proposed the ultrasonic positioning system without synchronizing RF. The proposed system is based on existing USAT (Ultrasonic Satellite System) adopted infrastructure transmitting type, and consists of transmitter and receiver synchronizing modules instead of the radio frequency transmitters and receiver. The ultrasonic transmitters and receivers are synchronized individually by the transmitter and receiver synchronizing modules. In order to calculate the bias between the transmitter and receiver synchronizing modules, new positioning algorithm similar to GPS was proposed. The positioning performance of the improved USAT without synchronizing RF and the validity of the proposed positioning algorithm are verified and evaluated by experiments.

An Optimal FIR Filter for Discrete Time-varying State Space Models

Abstract: In this paper, an optimal FIR (Finite-Impulse-Response) filter is proposed for discrete time-varying state-space models. The proposed filter estimates the current state using measured output samples on the recent time horizon so that the variance of the estimation error is minimized. It is designed to be linear, unbiased, with an FIR structure, and is independent of any state information. Due to its FIR structure, the proposed filter is believed to be robust for modeling uncertainty or numerical errors than other IIR filters, such as the Kalman filter. For a general system with system and measurement noise, the proposed filter is derived without any artificial assumptions such as the nonsingular assumption of the system matrix A and any infinite covariance of the initial state. A numerical example show that the proposed FIR filter has better performance than the Kalman filter based on the IIR (Infinite- Impulse-Response) structure when modeling uncertainties exist.

A Path Generation Algorithm for Obstacle Avoidance in Waypoint Navigation of Unmanned Ground Vehicle

Abstract: In this paper, an effective path generation algorithm for obstacle avoidance producing small amount of steering action as possible is proposed. The proposed path generation algorithm can reduce unnecessary steering because of the small lateral changes in generated waypoints when UGV (Unmanned Ground Vehicle) encounters obstacles during its waypoint navigation. To verify this, the proposed algorithm and algorithm are analyzed through the simulation. The proposed algorithm shows good performance in terms of lateral changes in the generated waypoint, steering changes of the vehicle while driving and execution speed of the algorithm. Especially, due to the fast execution speed of the algorithm, the obstacles that encounter suddenly in front of the vehicle within short range can be avoided. This algorithm consider the waypoint navigation only. Therefore, in certain situations, the algorithm may generate the wrong path. In this case, a general path generation algorithm like is used instead. However, these special cases happen very rare during the vehicle waypoint navigation, so the proposed algorithm can be applied to most of the waypoint navigation for the unmanned ground vehicle.

Geometrical Featured Voxel Based Urban Structure Recognition and 3-D Mapping for Unmanned Ground Vehicle

Abstract: Recognition of structures in urban environments is a fundamental ability for unmanned ground vehicles. In this paper we propose the geometrical featured voxel which has not only 3-D coordinates but also the type of geometrical properties of point cloud. Instead of dealing with a huge amount of point cloud collected by range sensors in urban, the proposed voxel can efficiently represent and save 3-D urban structures without loss of geometrical properties. We also provide an urban structure classification algorithm by using the proposed voxel and machine learning techniques. The proposed method enables to recognize urban environments around unmanned ground vehicles quickly. In order to evaluate an ability of the proposed map representation and the urban structure classification algorithm, our vehicle equipped with the sensor system collected range data and pose data in campus and experimental results have been shown in this paper.

예지기술의 연구동향 및 모델기반 예지기술 비교연구

Abstract: In this paper, PHM (Prognostics and Health Management) techniques are briefly outlined. Prognostics, being a central step within the PHM, is explained in more detail, stating that there are three approaches ? experience based, data-driven and model based approaches. Representative articles in the field of prognostics are also given in terms of the type of faults. Model based method is illustrated by introducing a case study that was conducted to the crack growth of the gear plate in UH-60A helicopter. The paper also addresses the comparison of the OBM (Overall Bayesian Method), which was developed by the authors with the PF (Particle Filtering) method, which draws great attention recently in prognostics, through the study on a simple crack growth problem. Their performances are examined by evaluating the metrics introduced by PHM society.

Design of Complementary Filter using Least Square Method

Abstract: This paper shows a method to design complementary filter using least square. The complementary filter is one of useful filters estimating angle. The basic concept of this filter is to enhance advantages of each sensor that angle detecting using a gyroscope has good accuracy at a high frequency and an accelerometer at a low frequency. When designing complementary filter, the most commonly used method is using cut-off frequency. However, it may be not easy to obtain a cut-off frequency. This paper presents a systematic method to determine the coefficients of the complementary filter using well-known linear least squares minimizing error between estimating angle and true angle.

The Development of Sensor System and 3D World Modeling for Autonomous Vehicle

Abstract: 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.

Design of Nonlinear Disturbance Observer Guaranteeing Global Stability and Robust Stability Condition

Abstract: A nonlinear version of disturbance observer is presented. The system under consideration is an uncertain single input single output nonlinear system and the nominal plant is also a nonlinear system. Compared to the previous implementation given in [8], the proposed scheme does not require an auxiliary variable anymore, thus it has a simpler and more intuitive structure. A robust stability condition for the overall closed-loop system is also provided.

Intelligent Controller for Networked Control Systems with Time-delay

Abstract: We consider the stabilization problem for a class of networked control systems with random delays in the discrete-time domain. The controller-to-actuator and sensor-to-controller time-delays are modeled as two Markov chains, and the resulting closed-loop systems are Markovian jump nonlinear systems with two modes. The T-S (Takagi-Sugeno) fuzzy model is employed to represent a nonlinear system with Markovian jump parameters. The aim is to design a fuzzy controller such that the closed-loop Markovian jump fuzzy system is stochastically stable. The necessary and sufficient conditions on the existence of stabilizing fuzzy controllers are established in terms of LMIs (Linear Matrix Inequalities). It is shown that fuzzy controller gains are mode-dependent. Finally, a simulation example is presented to illustrate the effectiveness of the proposed design method.

Stereo-Vision Based Road Slope Estimation and Free Space Detection on Road

Abstract: This paper presents an algorithm capable of detecting free space for the autonomous vehicle navigation The algorithm consists of two main steps: 1) estimation of longitudinal profile of road, 2) detection of free space The estimation of longitudinal profile of road is detection of v-line in v-disparity image which is corresponded to road slope, using v-disparity image and hough transform, Dijkstra algorithm To detect free space, we detect u-line in u-disparity image which is a boundary line between free space and obstacle`s region, using u-disparity image and dynamic programming Free space is decided by detected v-line and u-line The proposed algorithm is proven to be successful through experiments under various traffic scenarios

Development of Cylindrical-type Finger Force Measuring System Using Two-axis Force/Moment Sensor and its Characteristic Evaluation

Abstract: Some patients can`t use their hands because of inherent and acquired paralysis of their fingers. Their fingers can recover with rehabilitative training, and the extent of rehabilitation can be judged by grasping a cylindrical-object with their fingers. At present, the cylindrical-object used in hospitals is only a cylinder which cannot measure grasping force of the fingers. Therefore, doctors must judge the extent of rehabilitation by watching patients` fingers as they grasp the cylinder. A cylindrical-type finger force measuring system which can measure the grasping force of patients` fingers should be developed. This paper looks at the development of a cylindrical-type finger force measuring system with two-axis force/moment sensor which can measure grasping force. The two-axis force/moment sensor was designed and fabricated, and the high-speed force measuring device was designed and manufactured by using DSP (digital signal processing). Also, cylindrical-type finger force measuring system was developed using the developed two-axis force/moment sensor and the high-speed force measuring device, and the grasping force tests of men were performed using the developed system. The tests confirm that the average finger forces of right and left hands for men were about 186N and 172N respectively.

Bezier Curve-Based Path Planning for Robust Waypoint Navigation of Unmanned Ground Vehicle

Abstract: This paper presents a sensor fusion-based estimation of heading and a Bezier curve-based motion planning for unmanned ground vehicle. For the vehicle to drive itself autonomously and safely, it should estimate its pose with sufficient accuracy in reasonable processing time. The vehicle should also have a path planning algorithm that enables to adapt to various situations on the road, especially at intersections. First, we address a sensor fusion-based estimation of the heading of the vehicle. Based on extended Kalman filter, the algorithm estimates the heading using the GPS, IMU, and wheel encoders considering the reliability of each sensor measurement. Then, we propose a Bezier curve-based path planner that creates several number of path candidates which are described as Bezier curves with adaptive control points, and selects the best path among them that has the maximum probability of passing through waypoints or arriving at target points. Experiments under various outdoor conditions including at intersections, verify the reliability of our algorithm.

HSA-based HMM Optimization Method for Analyzing EEG Pattern of Motor Imagery

Abstract: HMMs (Hidden Markov Models) are widely used for biological signal, such as EEG (electroencephalogram) sequence, analysis because of their ability to incorporate sequential information in their structure. A recent trends of research are going after the biological interpretable HMMs, and we need to control the complexity of the HMM so that it has good generalization performance. So, an automatic means of optimizing the structure of HMMs would be highly desirable. In this paper, we described a procedure of classification of motor imagery EEG signals using HMM. The motor imagery related EEG signals recorded from subjects performing left, right hand and foots motor imagery. And the proposed a method that was focus on the validation of the HSA (Harmony Search Algorithm) based optimization for HMM. Harmony search algorithm is sufficiently adaptable to allow incorporation of other techniques. A HMM training strategy using HSA is proposed, and it is tested on finding optimized structure for the pattern recognition of EEG sequence. The proposed HSA-HMM can performs global searching without initial parameter setting, local optima, and solution divergence.

Lane Marking Detection of Mobile Robot with Single Laser Rangefinder

Abstract: 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.

FPD 공정용 Glass 이송 시스템을 위한 자기부상 EMS의 개발

Abstract: 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 ±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.

T-S Fuzzy Model-based Waypoints-Tracking Control of Underwater Vehicles

Abstract: 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.

A Recommendation System Based-on Interactive Evolutionary Computation with Data Grouping

Abstract: Recently, recommender systems have been widely applied in E-commerce websites to help their customers find the items what they want. A recommender system should be able to provide users with useful information regarding their interests. The ability to immediately respond to the changes in user`s preference is a valuable asset of recommender systems. This paper proposes a novel recommender system which aims to effectively adapt and respond to the immediate changes in user`s preference. The proposed system combines IEC (Interactive Evolutionary Computation) with a content-based filtering method and also employs data grouping in order to improve time efficiency. Experiments show that the proposed system makes acceptable recommendations while ensuring quality and speed. From a comparative experimental study with an existing recommender system which uses the content-based filtering, it is revealed that the proposed system produces more reliable recommendations and adaptively responds to the changes in any given condition. It denotes that the proposed approach can be an alternative to resolve limitations (e.g., over-specialization and sparse problems) of the existing methods.

Efficient Object Tracking System Using the Fusion of a CCD Camera and an Infrared Camera

Abstract: To make a robust object tracking and identifying system for an intelligent robot and/or home system, heterogeneous sensor fusion between visible ray system and infrared ray system is proposed. The proposed system separates the object by combining the ROI (Region of Interest) estimated from two different images based on a heterogeneous sensor that consolidates the ordinary CCD camera and the IR (Infrared) camera. Human`s body and face are detected in both images by using different algorithms, such as histogram, optical-flow, skin-color model and Haar model. Also the pose of human body is estimated from the result of body detection in IR image by using PCA algorithm along with AdaBoost algorithm. Then, the results from each detection algorithm are fused to extract the best detection result. To verify the heterogeneous sensor fusion system, few experiments were done in various environments. From the experimental results, the system seems to have good tracking and identification performance regardless of the environmental changes. The application area of the proposed system is not limited to robot or home system but the surveillance system and military system.