• Journal of Information Processing Systems
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• v.7 no.1
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• pp.17-28
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• 2011

Despite the fact that the deployment of sensor networks and target tracking could both be managed by taking full advantage of Voronoi diagrams, very little few have been made in this regard. In this paper, we designed an optimized barrier coverage and an energy-efficient clustering algorithm for forming Vonoroi-based Wireless Sensor Networks(WSN) in which we proposed a mobile target tracking scheme (CTT&MAV) that takes full advantage of Voronoi-diagram boundary to improve detectability. Simulations verified that CTT&MAV outperforms random walk, random waypoint, random direction and Gauss-Markov in terms of both the average hop distance that the mobile target moved before being detected and lower sensor death rate. Moreover, we demonstrate that our results are robust as realistic sensing models and also validate our observations through extensive simulations.

• Journal of the Korea Society of Computer and Information
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• v.24 no.4
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• pp.57-63
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• 2019

In this paper, we propose a new framework to control VR(Virtual reality) contents in real time using user's mouth-wind and acceleration sensor of mobile device. In VR, user interaction technology is important, but various user interface methods is still lacking. Most of the interaction technologies are hand touch screen touch or motion recognition. We propose a new interface technology that can interact with VR contents in real time using user's mouth-wind method with acceleration sensor. The direction of the mouth-wind is determined using the angle and position between the user and the mobile device, and the control position is adjusted using the acceleration sensor of the mobile device. Noise included in the size of the mouth wind is refined using a simple average filter. In order to demonstrate the superiority of the proposed technology, we show the result of interacting with contents in game and simulation in real time by applying control position and mouth-wind external force to the game.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.7-12
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• 1992

This paper proposes a sensor-based path planning method which utilizes fuzzy logic and neural network for obstacle avoidance of a mobile robot in uncertain environments. In order to acquire the information about the environment around the mobile robot, the ultrasonic sensors mounted on the front of mobile robot are used. The neural network, whose inputs are preprocessed by ultrasonic sensor readings, informs the mobile robot of the situation of environment in which mobile robot is at the present instant. Then, according to the situation class, the fuzzy rules are fired to make a decision on the mobile robot action. In addition, this method can be implemented real time since the number of fuzzy rules used to avoid the obstacle is small. Fuzzy rules are constructed based on the human reasoning and tuned by iterative simulations. The effective of the proposed avoidance method is verified by a series of simulations.

• Journal of Internet Technology
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• v.22 no.2
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• pp.297-309
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• 2021

Mobile sinks are being exploited for various purposes for solving the hotspot problem. Thus, the mobility support technique of mobile sinks is important, and it has been studied steadily. A survey was conducted of studies of mobile sinks in sensor networks having different movement patterns depending on the applications. The related techniques were divided into three main categories according to mobility pattern: predefined, random, and control. In addition, communications for mobile sinks are strongly affected by whether there is a single mobile sink or multiple ones. Based on this two-level categorization, an overview is presented of some state-of-the-art mobility support techniques researched during the past three years, and then the technique are analyzed according to various criteria. Finally, this survey concludes with a summary and a discussion of some future research challenges.

• The KIPS Transactions:PartC
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• v.16C no.6
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• pp.737-746
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• 2009

Given the increased interest in ubiquitous computing, wireless sensor network has been researched widely. The localization service which provides the location information of mobile user, is one of important service provided by sensor network. Many methods to obtain the location information of mobile user have been proposed. However, these methods were developed for only one mobile user so that it is hard to extend for multiple mobile users. If multiple mobile users start the localization process concurrently, there could be interference of beacon or ultrasound that each mobile user transmits. In the paper, we propose APL(Adaptive Power Control based Resource Allocation Technique for Efficient Localization Technique), the localization technique for multiple mobile nodes based on adaptive power control in mobile wireless sensor networks. In APL, collision of localization between sensor nodes is prevented by forcing the mobile node to get the permission of localization from anchor nodes. For this, we use RTS(Ready To Send) packet type for localization initiation by mobile node and CTS(Clear To Send) packet type for localization grant by anchor node. NTS(Not To Send) packet type is used to reject localization by anchor node for interference avoidance and STS(Start To Send) for synchronization between 모anchor nodes. At last, the power level of sensor node is controled adaptively to minimize the affected area. The experimental result shows that the number of interference between nodes are increased in proportion to the number of mobile nodes and APL provides efficient localization.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.4
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• pp.381-390
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• 2010

This paper describes a procedure of the map-based localization for mobile robots by using a sensor fusion technique in structured environments. A combination of various sensors with different characteristics and limited sensibility has advantages in view of complementariness and cooperation to obtain better information on the environment. In this paper, for robust self-localization of a mobile robot with a monocular camera and a laser structured light sensor, environment information acquired from two sensors is combined and fused by a Bayesian sensor fusion technique based on the probabilistic reliability function of each sensor predefined through experiments. For the self-localization using the monocular vision, the robot utilizes image features consisting of vertical edge lines from input camera images, and they are used as natural landmark points in self-localization process. However, in case of using the laser structured light sensor, it utilizes geometrical features composed of corners and planes as natural landmark shapes during this process, which are extracted from range data at a constant height from the navigation floor. Although only each feature group of them is sometimes useful to localize mobile robots, all features from the two sensors are simultaneously used and fused in term of information for reliable localization under various environment conditions. To verify the advantage of using multi-sensor fusion, a series of experiments are performed, and experimental results are discussed in detail.

• Journal of the Korea Society of Computer and Information
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• v.13 no.7
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• pp.139-148
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• 2008

The sensor network is applied from the field which is various. The sensor network nodes are exchanged with mobile environment and they construct they select cluster and cluster headers. In this paper, we propose the Dynamic Prediction Clustering Algorithm use to Skyline queries attributes in direction, angel and hop. This algorithm constructs cluster in base mobile sensor node after select cluster header. Propose algorithm is based made cluster header for mobile sensor node. It "Adv" reduced the waste of energy which mobile sensor node is unnecessary. Respects clustering where is efficient according to hop count of sensor node made dynamic cluster. To extend a network life time of 2.4 times to decrease average energy consuming of sensor node. Also maintains dynamic cluster to optimize the within hop count cluster, the average energy specific consumption of node decreased 14%.

• Journal of Computing Science and Engineering
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• v.9 no.4
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• pp.163-176
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• 2015

Self-organization of distributed wireless sensor nodes is a critical issue in wireless sensor networks (WSNs), since each sensor node has limited energy, bandwidth, and scalability. These issues prevent sensor nodes from actively collaborating with the other types of sensor nodes deployed in a typical heterogeneous and somewhat hostile environment. The automated self-organization of a WSN becomes more challenging as the number of sensor nodes increases in the network. In this paper, we propose a dynamic self-organized architecture that combines tree topology with a drawn-grid algorithm to automate the self-organization process for WSNs. In order to make our proposed architecture scalable, we assume that all participating active sensor nodes are unaware of their primary locations. In particular, this paper presents two algorithms called active-tree and drawn-grid. The proposed active-tree algorithm uses a tree topology to assign node IDs and define different roles to each participating sensor node. On the other hand, the drawn-grid algorithm divides the sensor nodes into cells with respect to the radio coverage area and the specific roles assigned by the active-tree algorithm. Thus, both proposed algorithms collaborate with each other to automate the self-organizing process for WSNs. The numerical and simulation results demonstrate that the proposed dynamic architecture performs much better than a static architecture in terms of the self-organization of wireless sensor nodes and energy consumption.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.5
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• pp.291-299
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• 2005

An obstacle avoidance algorithm for a network-based autonomous mobile robot is proposed in this paper. The obstacle avoidance algorithm is based on the VFH(Vector Field Histogram) algorithm and two delay compensation methods with the VFH algorithm are proposed for a network-based robot with distributed environmental sensors, mobile actuators, and the VFH controller. Firstly, the environmental sensor information is compensated by prospection with acquired environmental sensor information, measured network delays, and the kinematic model of the robot. The compensated environmental sensor information is used for building polar histogram with the VFH algorithm. Secondly, a sensor fusion algorithm for localization of the robot is proposed to compensate the delay of odometry sensor information and the delay of environmental sensor information. Through some simulation tests, the performance enhancement of the proposed algorithm in the viewpoint of efficient path generation and accurate goal positioning is shown here.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.1 s.94
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• pp.253-264
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• 1999

Most autonomous mobile robots view only things in front of them, and as a result, they may collide with objects moving from the side or behind. To overcome this problem. an Active Omni-directional Range Sensor System has been built that can obtain an omni-directional range data through the use of a laser conic plane and a conic mirror. Also, mobile robot has to know its current location and heading angle by itself as accurately as possible to successfully navigate in real environments. To achieve this capability, we propose a self-localization algorithm of a mobile robot using an active omni-directional range sensor in an unknown environment. The proposed algorithm estimates the current position and head angle of a mobile robot by a registration of the range data obtained at two positions, current and previous. To show the effectiveness of the proposed algorithm, a series of simulations was conducted and the results show that the proposed algorithm is very efficient, and can be utilized for self-localization of a mobile robot in an unknown environment.