• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.107-109
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• 2004

In this paper, authors propose the sensor fusion system that can recognize multiple 3D objects from 2D projection images and tactile information. The proposed system focuses on improving recognition performance of 3D object. Unlike the conventional object recognition system that uses image sensor alone, the proposed method uses tactual sensors in addition to visual sensor. Neural network is used to fuse these informations. Tactual signals are obtained from the reaction force by the pressure sensors at the fingertips when unknown objects are grasped by four-fingered robot hand. The experiment evaluates the recognition rate and the number of teaming iterations of various objects. The merits of the proposed systems are not only the high performance of the learning ability but also the reliability of the system with tactual information for recognizing various objects even though visual information has a defect. The experimental results show that the proposed system can improve recognition rate and reduce learning time. These results verify the effectiveness of the proposed sensor fusion system as recognition scheme of 3D object.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.4
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• pp.707-714
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• 2019

Recently, as the sensor network technologies and camera technologies develops, there are increasing needs by combining two technologies to effectively observe or monitor the areas that are difficult for people to access by using the visual sensor network. Since the applications using visual sensors take pictures of the outdoor areas, the images may not be well contrasted due to cloudy weather or low-light time periods such as a sunset. In this paper, we first model the color characteristics according to illumination using the characteristics of visual sensors that continuously capture the same area. Using this model, a new method for improving low contrast images in real time is proposed. In order to make the model, the regions of interest consisting of the same color are set up and the changes of color according to the brightness of images are measured. The gamma function is used to model color characteristics using the measured data. It is shown by experimental results that the proposed method improves the contrast of an image by adjusting the color components of the low contrast image simply and accurately.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.146.3-146
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• 2001

It has been integrated into several navigation systems. This paper shows that system recognizes difficult indoor roads and open area without any specific mark such as painted guide tine or tape. In this method, Robot navigates with visual sensors, which uses visual information to navigate itself along the road. An Artificial Neural Network System was used to decide where to move. It is designed with USB web camera as visual sensor.

• Journal of Digital Convergence
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• v.14 no.8
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• pp.261-267
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• 2016

In this paper, we studied the range-free localization algorithm between sensor nodes based on the Radical Line for sensor networks. Routing in wireless sensor networks should reduce the overall energy consumption of the sensor network, or induce equivalent energy consumption of all the sensor nodes. In particular, when the amount of data to send more data, the energy consumption becomes worse. New methods have been proposed to address this. So as to allow evenly control the overall energy consumption. For this, the paper covers designing a localization algorithm that can obtain the location information of the peripheral nodes with fewer operations. For the operation of the algorithm is applicable Radical Line. The experimental environment is windows 7, the Visual C ++ 2010, MSSQL 2008. The experimental results could be localized to perform an error rate of 0.1837.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.5
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• pp.1400-1420
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• 2012

Object detection and tracking using visual sensors is a critical component of surveillance systems, which presents many challenges. This paper addresses the enhancement of object detection and tracking via the combination of multiple visual sensors. The enhancement method we introduce compensates for missed object detection based on the partial detection of objects by multiple visual sensors. When one detects an object or more visual sensors, the detected object's local positions transformed into a global object position. Local and global information exchange allows a missed local object's position to recover. However, the exchange of the information may degrade the detection and tracking performance by incorrectly recovering the local object position, which propagated by false object detection. Furthermore, local object positions corresponding to an identical object can transformed into nonequivalent global object positions because of detection uncertainty such as shadows or other artifacts. We improved the performance by preventing the propagation of false object detection. In addition, we present an evaluation method for the final global object position. The proposed method analyzed and evaluated using case studies.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.346-349
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• 2004

The teleoperation system applies all of the industrial fields due to the development of the network infrastructure. It is one of the indispensable elements for controlling the robot at a remote sight and monitoring the limit or unknown environment. The common teleoperation robot system is what has the visual module to supply the network system and realistic UI to the existed robot system. Therefore, remarked that the fusion between modules and transmission of visual data the remarked the important element to improve the robot application in the various environments. Delay of development time by robot platform and noneffective communication among developers are also problem to approach. In this paper we propose the independent teleoperation system. The main application language is JAVA in this system, which is applied JAVA API like JNI and JMF to construct the effective teleoperation system. The system has the both side communication system between sever and client as a basic structure. The visual data that is attached the robot at a remote sight is captured by JMF API and then is transmitted to the web browser called client by RTR protocol. JNI is used to connect between JAVA and the lower part application (sensor fusion, motion control.) of the robot programmed by various Native languages. The proposed system is the application that can perform the elements, for instance transmission of visual data, the fusion of various native application modules and the effective network communication, with any platform.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.474-474
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• 2000

This paper shows that a system with two-link arm can obtain hand reaching movement to a target object projected on a visual sensor by reinforcement learning using a layered neural network. The reinforcement signal, which is an only signal from the environment, is given to the system only when the hand reaches the target object. The neural network computes two joint torques from visual sensory signals, joint angles, and joint angular velocities considering the urn dynamics. It is known that the trajectory of the voluntary movement o( human hand reaching is almost straight, and the hand velocity changes like bell-shape. Although there are some exceptions, the properties of the trajectories obtained by the reinforcement learning are somewhat similar to the experimental result of the human hand reaching movement.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.5
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• pp.739-744
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• 2013

In the past several years there has been increasing the studies using ubiquitous technology as the base technology of IT-convergence. The cooltown, one of the ubiquitous projects, is based on the web technology and the mobile environment. However, in the cooltown system, users only get a pre-made web-page. In this paper, we propose the algorithm improved usability applying the context-awareness based on the sensor network. In this paper, we can provide a custom tailored service overlooked in the existing system from this.

• The Journal of Korea Robotics Society
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• v.4 no.3
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• pp.177-184
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• 2009

This paper presents an active assisted-living system in wireless sensor and actor network (WSAN) in which the mobile robot roles an actor. In order to provide assisted-living service to the elderly people, position recognition of the sensor node attached on the user and localization of the mobile robot should be performed at the same time. For the purpose, we use received signal strength indication (RSSI) to find the position of the person and ubiquitous sensor nodes including ultrasonic sensor which performs both transmission of sensor information and localization like global positioning system. Active services are moving to the elderly people by detecting activity sensor and visual tracking and voice chatting with remote monitoring system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.135-138
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• 2009

G-Sensor is being used for controlling motion of smart-phone and robot. G-Sensor can control motion to several direction, because it is composed of X, Y, and Z axis and also can be used on many mobile-phone by using Wi-Fi communication and RS-232C communication on the Bluetooth module. In this research, we suggest the application that realize and develop visual-vehicle-remote-control-system by using mobile-phone with G-Sensor so that drivers can more easily remote control and manage their vehicle with mobile-phone in real-time visual.