• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.5 no.6
• /
• pp.1163-1168
• /
• 2001

The ranging systems measure range data in three-dimensional coordinate from target surface. These non-contact remote ranging systems is widely used in various automation applications, including military equipment, construction field, navigation, inspection, assembly, and robot vision. The active ranging systems using time of flight technique or light pattern illumination technique are complex and expensive, the passive systems based on stereo or focusing principle are time-consuming. The proposed algorithm, that is based on cross correlation of projection profile of vertical edge, provides advantages of fast and simple operation in the range acquisition. The results of experiment show the effectiveness of the proposed algorithm.

• Journal of Institute of Control, Robotics and Systems
• /
• v.16 no.12
• /
• pp.1226-1232
• /
• 2010

A door can serve as a feature for place classification and localization for navigation of a mobile robot in indoor environments. This paper proposes a door detection method based on the recognition of various door handles using the general Hough transform (GHT) and support vector machine (SVM). The contour and color histogram of a door handle extracted from the database are used in GHT and SVM, respectively. The door recognition scheme consists of four steps. The first step determines the region of interest (ROI) images defined by the color information and the environment around the door handle for stable recognition. In the second step, the door handle is recognized using the GHT method from the ROI image and the image patches are extracted from the position of the recognized door handle. In the third step, the extracted patch is classified whether it is the image patch of a door handle or not using the SVM classifier. The door position is probabilistically determined by the recognized door handle. Experimental results show that the proposed method can recognize various door handles and detect doors in a robust manner.

• Journal of information and communication convergence engineering
• /
• v.7 no.2
• /
• pp.119-124
• /
• 2009

In this paper, we propose a novel approach to estimating the real-time moving trajectory of an object is proposed in this paper. The object's position is obtained from the image data of a CCD camera, while a state estimator predicts the linear and angular velocities of the moving object. To overcome the uncertainties and noises residing in the input data, a Extended Kalman Filter(EKF) and neural networks are utilized cooperatively. Since the EKF needs to approximate a nonlinear system into a linear model in order to estimate the states, there still exist errors as well as uncertainties. To resolve this problem, in this approach the Kohonen networks, which have a high adaptability to the memory of the input-output relationship, are utilized for the nonlinear region. In addition to this, the Kohonen network, as a sort of neural network, can effectively adapt to the dynamic variations and become robust against noises. This approach is derived from the observation that the Kohonen network is a type of self-organized map and is spatially oriented, which makes it suitable for determining the trajectories of moving objects. The superiority of the proposed algorithm compared with the EKF is demonstrated through real experiments.

• Proceedings of the KIEE Conference
• /
• 2004.07d
• /
• pp.2206-2208
• /
• 2004

본 논문에서는 자이로스코프를 이용한 자율이동로봇의 주행기록계에 대한 오차 보상을 제안한다. 자율이동로봇의 주행 시 주행기록계는 슬립과 마찰 등으로 인해 많은 방향각에 대해 오차를 포함하고 있어서 주행기록계에만 의존하여 주행하기 힘들다. 주행기록계가 슬립과, 회전에 대한 단점을 보안하기 위해 방향각에 대해 자이로스코프를 사용하여, 자이로스코프로부터 얻은 데이터와 주행기록계의 데이터를 융합하여 주행기록계의 오차누적에 의한 이동로봇의 방향각에 대한 비정확성을 보상하기 위한 알고리듬을 제안한다. 대부분의 주행 시 주행기록계의 값을 신뢰하고 자율이동로봇의 순간적인 각도변화에 대해서는 자이로스코프를 이용하였다. 이동로봇의 직진 주행 실험 결과 주행기록계만을 사용하여 주행했을 때는 방향각 오차가 크게 발생하였다. 그러나 주행기록계와 자이로스코프의 데이터를 융합하여 적용한 시스템의 성능이 주행기록계만 이용한 경우에 비해 보다 정확함을 실험을 통해 확인하였다. 이동로봇의 안정성 있는 경로 추종을 통해 이동로봇의 보다 넓은 영역에서의 작업이 기대된다.

• Journal of Institute of Control, Robotics and Systems
• /
• v.19 no.9
• /
• pp.797-804
• /
• 2013

In this paper, a study of a new hovering six dof underwater robot with redundant horizontal thrusters, titled HAUV (hovering AUV), is presented. The results of study on the structure design, deployment of thrusters, and development of the developed control system of the AUV was presented. For the HAUV structure, a structure design and an analysis of the thrusting system was performed. For navigation, a sensor fusion board which can proceed various sensor signals to identify correct positions and speeds was developed and a total control system including EKF (Extended Kalman Filter) was designed. Rolling, pitching and depth control tests of the HAUV have been performed, and relatively small angle error and depth tracking error results were shown.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.12 no.1
• /
• pp.123-128
• /
• 2017

This paper deals with performing missions through autonomous navigation using camera and other sensors. Extracting pose of the car is necessary to navigate safely within the given road. Homography is used to find it. Color image is converted into grey image and thresholding and edge is used to find control points. Two control ponits are converted into world coordinates using homography to find the angle and position of the car. Color is used to find traffic signal. It was confirmed that the given tasks performed well through experiments.

• Journal of Institute of Control, Robotics and Systems
• /
• v.12 no.7
• /
• pp.693-699
• /
• 2006

An accurate and compact map is essential to an autonomous mobile robot system. For navigation, it is efficient to use an occupancy grid map because the environment is represented by probability distribution. But it is difficult to apply it to the large environment since it needs a large amount of memory proportional to the environment size. As an alternative, a topological map can be used to represent it in terms of the discrete nodes with edges connecting them. It is usually constructed by the Voronoi-like graphs, but in this paper the topological map is incrementally built based on the local grid map using the thinning algorithm. This algorithm can extract only meaningful topological information by using the C-obstacle concept in real-time and is robust to the environment change, because its underlying local grid map is constructed based on the Bayesian update formula. In this paper, the position probability is defined to evaluate the quantitative reliability of the end nodes of this thinning-based topological map (TTM). The global TTM can be constructed by merging each local TTM by matching the reliable end nodes determined by the position probability. It is shown that the proposed TTM can represent the environment accurately in real-time and it is readily extended to the global TTM.

• Journal of the Korean Society for Precision Engineering
• /
• v.26 no.6
• /
• pp.74-80
• /
• 2009

Path tracking of unmanned vehicle is a basis of autonomous driving and navigation. For the path tracking, it is very important to find the exact position of a vehicle. GPS is used to get the position of vehicle and a direction sensor and a velocity sensor is used to compensate the position error of GPS. To detect path lines in a road image, the bird's eye view transform is employed, which makes it easy to design a lateral control algorithm simply than from the perspective view of image. Because the driving speed of vehicle should be decreased at a curved lane and crossroads, so we suggest the speed control algorithm used GPS and image data. The control algorithm is simulated and experimented from the basis of expert driver's knowledge data. In the experiments, the results show that bird's eye view transform are good for the steering control and a speed control algorithm also shows a stability in real driving.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.13 no.2
• /
• pp.140-146
• /
• 2013

In this paper, we describe a vision sensor-based driving algorithm for indoor automatic guided vehicles (AGVs) that facilitates a path tracking task using two mono cameras for navigation. One camera is mounted on vehicle to observe the environment and to detect markers in front of the vehicle. The other camera is attached so the view is perpendicular to the floor, which compensates for the distance between the wheels and markers. The angle and distance from the center of the two wheels to the center of marker are also obtained using these two cameras. We propose five movement patterns for AGVs to guarantee smooth performance during path tracking: starting, moving straight, pre-turning, left/right turning, and stopping. This driving algorithm based on two vision sensors gives greater flexibility to AGVs, including easy layout change, autonomy, and even economy. The algorithm was validated in an experiment using a two-wheeled mobile robot.

• The Journal of Korea Robotics Society
• /
• v.9 no.2
• /
• pp.104-110
• /
• 2014

Mapping is a fundamental element for robotic services. There are available many types of map data representation such as grid map, metric map, topology map, etc. As more robots are deployed for services, more chances of exchanging map data among the robots emerge and standardization of map data representation (MDR) becomes more valuable. Currently, activities in developing MDR standard are underway in IEEE Robotics and Automation Society. The MDR standard is for a common representation and encoding of the two-dimensional map data used for navigation by mobile robots. The standard focuses on interchange of map data among components and systems, particularly those that may be supplied by different vendors. This paper aims to introduce MDR standard and its application to map merging. We have applied the basic structure of the MDR standard to a grid map and Voronoi graph as a kind of topology map and performed map merging between two different maps. Simulation results show that the proposed MDR is suitable for map data exchange among robots.