• Journal of Korea Society of Digital Industry and Information Management
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• v.7 no.4
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• pp.31-37
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• 2011

Recently, MANET(Mobile Ad-hoc Network) is developing increasingly in the wireless network. MANET has weakness because phases change frequently and MANET doesn't have middle management system. Every node which consists of MANET has to perform data forwarding, but traceback is not reliable if these nodes do malicious action owing to attack. It also is not easy to find location of attacker when it is attacked as moving of nodes. In this paper, we propose a hierarchical-based traceback method that reduce waste of memory and can manage path information efficiently. In order to manage trace path information and reduce using resource in the cluster head after network is formed to cluster, method which recomposes the path efficiently is proposed. Proposed method in this paper can reduce path trace failure rate remarkably due to moving of nodes. It can also reduce the cost for traceback and time it takes to collect information.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2325-2330
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• 2005

A potential field method for solving the problem of path planning based on global and local information for a mobile robot moving among a set of stationary obstacles is described. The concept of various method used path planning is used design a planning strategy. A real human living area is constructed by many moving and imminence obstacles. Home service mobile robot must avoid many obstacles instantly. A path that safe and attraction towards the goal is chosen. The potential function depends on distance from the goal and heuristic function relies on surrounding environments. Three additional combined methods are proposed to apply to human living area, calibration robots position by measured surrounding environment and adapted home service robots. In this work, we proposed the application of various path planning theory to real area, human living. First, we consider potential field method. Potential field method is attractive method, but that method has great problem called local minimum. So we proposed intermediate point in real area. Intermediate point was set in doorframe and between walls there is connect other room or other area. Intermediate point is very efficiency in computing path. That point is able to smaller area, area divided by intermediate point line. The important idea is intermediate point is permanent point until destruction house or apartment house. Second step is move robot with sensing on front of mobile robot. With sensing, mobile robot recognize obstacle and judge moving obstacle. If mobile robot is reach the intermediate point, robot sensing the surround of point. Mobile robot has data about intermediate point, so mobile robot is able to calibration robots position and direction. Third, we gave uncertainty to robot and obstacles. Because, mobile robot was motion and sensing ability is not enough to control. Robot and obstacle have uncertainty. So, mobile robot planed safe path planning to collision free. Finally, escape local minimum, that has possibility occur robot do not work. Local minimum problem solved by virtual obstacle method. Next is some supposition in real living area.

• IE interfaces
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• v.24 no.4
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• pp.447-456
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• 2011

Identifying the major moving patterns of shoppers' movements in the selling floor has been a longstanding issue in the retailing industry. With the advent of RFID technology, it has been easier to collect the moving data for a individual shopper's movement. Most of the previous studies used the traditional clustering technique to identify the major moving pattern of customers. However, in using clustering technique, due to the spatial constraint (aisle layout or other physical obstructions in the store), standard clustering methods are not feasible for moving data like shopping path should be adjusted for the analysis in advance, which is time-consuming and causes data distortion. To alleviate this problems, we propose a new approach to spatial pattern clustering based on longest common subsequence (LCSS). Experimental results using the real data obtained from a grocery in Seoul show that the proposed method performs well in finding the hot spot and dead spot as well as in finding the major path patterns of customer movements.

• IEMEK Journal of Embedded Systems and Applications
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• v.13 no.2
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• pp.65-71
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• 2018

In order to make the underwater vehicle carry out the mission in a submarine environment, it is needed to plan a safe and efficient route to a given destination and prevent the autonomous submersible from colliding with obstacles while moving along the planned route. The function of collision avoidance makes the travel distance of the autonomous submersible longer. Moreover, it should move slowly near to obstacles against their moving disturbance. As a result, this invokes the degradation of the navigation efficiency in the process of collision avoidance. The side effect of the collision avoidance is not ignorable in the case of high congested environments such as the coast with many obstacles. In this paper, we suggest a path planning method which provides the route with minimum travel time considering collision avoidance in congested environment. For the purpose, we define environmental congestion map related to geometric information and obstacles. And we propose a method to consider the moving cost in the RRT scheme that provides the existing minimum distance path. We verified that the efficiency of our algorithm with simulation experiments.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.1
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• pp.179-186
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• 2015

This paper proposes the target path detection algorithm using statistical characteristics of an activated time lag along a moving path of target from a neighboring sensor in PDR(Pulse Doppler Radar) sensor node environment based on USN(Ubiquitous Sensor Network) with a limitation detecting only an existence of moving target. In the proposed algorithm, detection and non-detection time lag obtained from the experimental data are used. The experimental data are through repetitive action of each 500 times about three path scenarios such as passing in between two sensors, moving parallel to two sensors, and turning through two sensors. From this experiments, error detection percentages of three path scenarios are 5.67%, 5.83%, and 7.17%, respectively. They show that the proposed algorithm can exactly detect a target path using the limited PDR sensor nodes.

• The Journal of the Korea Contents Association
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• v.12 no.9
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• pp.16-26
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• 2012

A path generation method considering the tendencies of users is required because users has the preferred routes through the properties such as time, distance, and congest. The existing method must input the additional information about user's tendency to generate path considering moving tendencies. However, mobile device have the inconvenient interface. Therefore users are reluctant to input additional information for path generation. In this paper, we propose the path generation method considering the tendencies of users without additional input of users tendencies. To show the superiority of the proposed method, we compared it with shortest distance or time path through performance evaluation.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1916-1917
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• 2011

A development of a new moving obstacle avoidance algorithm using a delay-time Compensation for a network-based autonomous mobile robot is proposed in this paper. The moving obstacle avoidance algorithm is based on a Kalman filter through moving obstacle estimation and a Bezier curve for path generation. And, the network-based mobile robot, that is a unified system composed of distributed environmental sensors, mobile actuators, and controller, is compensated by a network delay compensation algorithm for degradation performance by network delay. The network delay compensation method by a sensor fusion using the Kalman filter is proposed for the localization of the robot to compensate both the delay of readings of an odometry and the delay of reading of environmental sensors. Through some simulation tests, the performance enhancement of the proposed algorithm in the viewpoint of efficient path generation and accurate goal point is shown here.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.100-105
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• 1993

This paper discusses an approach to real-time path-planning of mobile robot navigating amidst multiple obstacles. Given an environment with the coordinates of known obstacles, the moving area of a mobile robot is divided into many patches of triangles with small edge length, in order to ensure a path better than those reported in the literature. After finding a minimum-distance to minimize the number of turns and total path-length by two-step path-revision and path-smmothing.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.55 no.2
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• pp.103-109
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• 2006

In this paper, the detection scheme of the spatial coordinates based on stereo camera for a intelligent path planning of an automatic mobile robot is proposed. In the proposed system, face area of a moving person is detected from a left image among the stereo image pairs by using the YCbCr color model and its center coordinates are computed by using the centroid method and then using these data, the stereo camera embedded on the mobile robot can be controlled for tracking the moving target in real-time. Moreover, using the disparity mad obtained from the left and right images captured by the tracking-controlled stereo camera system and the perspective transformation between a 3-D scene. and an image plane, depth information can be detected. Finally, based-on the analysis of these calculated coordinates, a mobile robot system is derived as a intelligent path planning and a estimation.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.4
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• pp.11-21
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• 2015

In order to achieve success in ground operations, searching for moving targets is one of critical factors. Usually, the system of searching for adversary ground moving targets has complex properties which includes target's moving characteristics, camouflage level, terrain, weather, available search time window, distance between target and searcher, moving speed, target's tactics, etc. The purpose of this paper is to present a practical quantitative method for effectively searching for infiltrated moving targets considering aforementioned complex properties. Based upon search theories, this paper consists of two parts. One is infiltration route analysis, through terrain and mobility analysis. The other is building dynamic probability maps through Monte Carlo simulation to determine the prioritized searching area for moving targets. This study primarily considers ground moving targets' moving pattern. These move by foot and because terrain has a great effect on the target's movement, they generally travel along a constrained path. With the ideas based on the terrain's effect, this study deliberately performed terrain and mobility analysis and built a constrained path. In addition, dynamic probability maps taking terrain condition and a target's moving speed into consideration is proposed. This analysis is considerably distinct from other existing studies using supposed transition probability for searching moving targets. A case study is performed to validate the effectiveness and usefulness of our methodology. Also, this study suggests that the proposed approach can be used for searching for infiltrated ground moving target within critical time window. The proposed method could be used not only to assist a searcher's mission planning, but also to support the tactical commander's timely decision making ability and ensure the operations' success.