• Proceedings of the KIEE Conference
• /
• 2008.10b
• /
• pp.331-332
• /
• 2008

A real-time path planning of mobile robots is a broad topic, covering a large spectrum of different technologies and applications. Briefly a path planning is designated moving technique from current pose to desired pose. It is remarkably easy to handle for human, not for robot. It is difficult that a robot recognizes surround to get a current pose and to avoid an obstacles. In this paper covers kinematics, path planning for efficient movements of a mobile robot. Kinematics of mobile robot which is suggested in this paper is exploited to create reliable and suitable motions. In addition, Gradient method is a algorithm which can guarantee for real-time path planning.

• Proceedings of the KIEE Conference
• /
• 2005.05a
• /
• pp.249-251
• /
• 2005

In this paper, an algorithm of path planning and obstacle avoidance for mobile robot is proposed. We call the proposed method Random Access Sequence(RAS) method. In the proposed method, a small region is set first and numbers are assigned to its neighbors. By processing assigned numbers all regions are covered and then the path from start to destination is selected by these numbers. The RAS has an advantage of fast planning because of simple operations. This implies that new path selection may be possible within a short time and helps a robot to avoid obstacles in any direction. The algorithm can be applied to unknown environments. When moving obstacles appear, a mobile robot avoids obstacles reactively. then new path is selected by RAS.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2013.04a
• /
• pp.476-481
• /
• 2013

Transfer path analysis(TPA) and operational deflection shape(ODS) have been widely utilized to analyze the characteristics of noise. TPA enables to decompose a noise into air-borne and structure-borne noises then estimate the path contribution of noise. ODS enables to analyze a moving shape and direction of interest components at a particular frequency. In this paper, TPA and ODS are applied to transfer paths of air-conditioner booming noise in a vehicle to reduce noise level, then a fixture is mounted it's path for distributing the high portion path contribution to the low portion path contribution. Through this experiment, the reduction of sound pressure level in air-conditioner booming noise is observed. Thereafter, TPA is again employed to verify the results of contribution.

• Journal of the military operations research society of Korea
• /
• v.18 no.2
• /
• pp.140-150
• /
• 1992

In this paper, we consider the shortest path problem of a Robot car moving in a workspace which consists of some obstacles. The motion of the Robot car is considered to have initial and final directions with some restrictions in the curvature of the path. At first we consider the problem in the case of having no obstacles and we give an analytical solution. Then wre present an algorithm to find a feasible path in the case of having obstacles and a method to improve this feasible path into a minimal path. Some computational results using Graph theory and Linear programming have been included.

• The KSFM Journal of Fluid Machinery
• /
• v.7 no.5 s.26
• /
• pp.7-12
• /
• 2004

Multi-path ultrasonic flowrate measuring technology is being received much attentions from a variety of industrial fields to exactly measure the flowrate. Multi-path ultrasonic flowmeter has much advantage since it has no moving parts and little pressure loss. It offers good accuracy, repeatability, linearity and turn-down ratio can be over 1:50. The present study investigates flowrate integration errors using weighting factors. A theoretical flow model uses power law to describe a fully developed velocity profiles and wall roughness is changed. Gaussian, Chebyshev, and Tailor methods are used to integrate line-average velocities. The obtained results show that Chebyshev method in 2, 4-path arrangement and Gaussian method in 3, 5-path arrangement are not affected for wall roughness changes.

• Journal of information and communication convergence engineering
• /
• v.8 no.2
• /
• pp.145-149
• /
• 2010

In this paper, we propose a kinematic approach to estimating the real-time moving object. A new scheme for a mobile robot to track and capture a moving object using images of a camera is proposed. The moving object is assumed to be a point-object and projected onto an image plane to form a geometrical constraint equation that provides position data of the object based on the kinematics of the active camera. Uncertainties in the position estimation caused by the point-object assumption are compensated using the Kalman filter. To generate the shortest time path to capture the moving object, the linear and angular velocities are estimated and utilized. The experimental results of tracking and capturing of the target object with the mobile robot are presented.

• The Journal of Korea Robotics Society
• /
• v.3 no.3
• /
• pp.212-218
• /
• 2008

Collision avoidance is a fundamental and important task of an autonomous mobile robot for safe navigation in real environments with high uncertainty. Obstacles are classified into static and dynamic obstacles. It is difficult to avoid dynamic obstacles because the positions of dynamic obstacles are likely to change at any time. This paper proposes a scheme for vision-based avoidance of dynamic obstacles. This approach extracts object candidates that can be considered moving objects based on the labeling algorithm using depth information. Then it detects moving objects among object candidates using motion vectors. In case the motion vectors are not extracted, it can still detect the moving objects stably through their color information. A robot avoids the dynamic obstacle using the dynamic window approach (DWA) with the object path estimated from the information of the detected obstacles. The DWA is a well known technique for reactive collision avoidance. This paper also proposes an algorithm which autonomously registers the obstacle color. Therefore, a robot can navigate more safely and efficiently with the proposed scheme.

• Journal of Institute of Control, Robotics and Systems
• /
• v.7 no.11
• /
• pp.933-938
• /
• 2001

In this paper, we describe a method for the mobile robot using images of a moving object. This method combines the observed position from dead-reckoning sensors and the estimated position from the images captured by a fixed camera to localize a mobile robot. Using the a priori known path of a moving object in the world coordinates and a perspective camera model, we derive the geometric constraint equations which represent the relation between image frame coordinates for a moving object and the estimated robot`s position. Since the equations are based on the estimated position, the measurement error may exist all the time. The proposed method utilizes the error between the observed and estimated image coordinates to localize the mobile robot. The Kalman filter scheme is applied to this method. Effectiveness of the proposed method is demonstrated by the simulation.

• International Journal of Internet, Broadcasting and Communication
• /
• v.10 no.4
• /
• pp.70-74
• /
• 2018

In order to ensure the flow of goods available and more flexible, reduce labor costs, many factories and industrial zones around the world are gradually moving to use automated solutions. One of them is to use Automated guided vehicles (AGV). Currently, there are a line tracing method as an AGV operating method, and a method of estimating the current position of the AGV and matching with a factory map and knowing the moving direction of the AGV. In this paper, we propose ceiling Light and guided line based moving direction estimation algorithm using multi-camera on the AGV in smart factory that can operate stable AGV by compensating the disadvantages of existing AGV operation method. The proposed algorithm is able to estimate its position and direction using a general - purpose camera instead of a sensor. Based on this, it can correct its movement error and estimate its own movement path.

• Journal of applied mathematics & informatics
• /
• v.14 no.1_2
• /
• pp.97-113
• /
• 2004

In this paper we shall study moving boundary problems, and we introduce an approach for solving a wide range of them by using calculus of variations and optimization. First, we transform the problem equivalently into an optimal control problem by defining an objective function and artificial control functions. By using measure theory, the new problem is modified into one consisting of the minimization of a linear functional over a set of Radon measures; then we obtain an optimal measure which is then approximated by a finite combination of atomic measures and the problem converted to an infinite-dimensional linear programming. We approximate the infinite linear programming to a finite-dimensional linear programming. Then by using the solution of the latter problem we obtain an approximate solution for moving boundary function on specific time. Furthermore, we show the path of moving boundary from initial state to final state.