• Journal of Institute of Control, Robotics and Systems
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• v.20 no.1
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• pp.78-86
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• 2014

This paper proposes a method of tracking an object for a person-following mobile robot by combining a monocular camera and a laser scanner, where each sensor can supplement the weaknesses of the other sensor. For human-robot interaction, a mobile robot needs to maintain a distance between a moving person and itself. Maintaining distance consists of two parts: object tracking and person-following. Object tracking consists of particle filtering and online learning using shape features which are extracted from an image. A monocular camera easily fails to track a person due to a narrow field-of-view and influence of illumination changes, and has therefore been used together with a laser scanner. After constructing the geometric relation between the differently oriented sensors, the proposed method demonstrates its robustness in tracking and following a person with a success rate of 94.7% in indoor environments with varying lighting conditions and even when a moving object is located between the robot and the person.

• 제어로봇시스템학회:학술대회논문집
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• 1986.10a
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• pp.317-320
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• 1986

A co-operative position control is proposed for two robot manipulators with 5 degree of freedoms to transfer an object following a specified trajectory, where each manipulator is assumed to change the posture of its end effector without releasing the object.

• Journal of the Korean Institute of Telematics and Electronics
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• v.24 no.4
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• pp.577-582
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• 1987

A co-operative position control is proposed for two robots manipulation with five degrees of freedom to transfer an object following a specified trajectory, where each manifulator is assumed to change the postrue of its end effector without releasing the object.

• The Journal of the Korea institute of electronic communication sciences
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• v.6 no.5
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• pp.765-773
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• 2011

This paper proposes a control method for a differential robot to track and follow a moving object based on ultrasonic sensor. To track a target object, the method uses a transmitter and two receivers to get distances from the object. The method derives translational and rotational error by the distances and then it uses the errors to calculate control values based on PID control method. The control values are used to control the robot to follow moving object. The authors do some experimentations to analyze some characteristics such as influence of PID gain, influence of translational and rotational gain. This method not only can be applied for following moving object problem but also can be done group unit control problems.

• Proceedings of the CALSEC Conference
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• 2003.09a
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• pp.249-254
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• 2003

Object caching is a desirable feature to improve the both scalability and performance of distributed application systems for information infrastructure, the information management system leveraging the power of network computing. However, in order to exploit such benefits, we claim that the following problems: cache server placement, cache replacement, and cache synchronization, should be considered when designing any object cache system. We are under developing DOC: a Distributed Object Caching, as a part of building our information infrastructures. In this paper, we show how each problem is inter-related, and focus to highlight how we handle cache server deployment problem

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.1
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• pp.101-110
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• 2004

The robots that will be needed in the near future are human-friendly robots that are able to coexist with humans and support humans effectively. To realize this, humans and robots need to be in close proximity to each other as much as possible. Moreover, it is necessary for their interactions to occur naturally. It is desirable for a robot to carry out human following, as one of the human-affinitive movements. The human-following robot requires several techniques: the recognition of the moving objects, the feature extraction and visual tracking, and the trajectory generation for following a human stably. In this research, a predictable intelligent space is used in order to achieve these goals. An intelligent space is a 3-D environment in which many sensors and intelligent devices are distributed. Mobile robots exist in this space as physical agents providing humans with services. A mobile robot is controlled to follow a walking human using distributed intelligent sensors as stably and precisely as possible. The moving objects 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 intelligent space. Uncertainties in the position estimation caused by the point-object assumption are compensated using the Kalman filter. To generate the shortest time trajectory to follow the walking human, the linear and angular velocities are estimated and utilized. The computer simulation and experimental results of estimating and following of the walking human with the mobile robot are presented.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.7
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• pp.966-973
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• 1995

In this paper, we compare several methods for implementing a VHDL design database through a case study on VHDL tool development system. We implemented three versions of the VHDL design database which the VHDL tool development system is based on. The first version was coded in the C programming language following value-oriented paradigm. The second one was coded in the C++ programming language following object-oriented paradigm. The third one was implemented using an existing object-oriented database. Based on our experience, we present quantitatively the pros and cons of each implementation method. The value-oriented version was most difficult to implement but showed good performance. Compared to the value- oriented version, the C++ version was twice as easy to implement and showed about the same performance. Using an existing object-oriented database allowed easiest implementation but resulted in a 1.5 to 6 times slower version.

• The Journal of Korea Robotics Society
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• v.3 no.1
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• pp.33-41
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• 2008

Based on object recognition technology, we present a new global localization method for robot navigation. For doing this, we model any indoor environment using the following visual cues with a stereo camera; view-based image features for object recognition and those 3D positions for object pose estimation. Also, we use the depth information at the horizontal centerline in image where optical axis passes through, which is similar to the data of the 2D laser range finder. Therefore, we can build a hybrid local node for a topological map that is composed of an indoor environment metric map and an object location map. Based on such modeling, we suggest a coarse-to-fine strategy for estimating the global localization of a mobile robot. The coarse pose is obtained by means of object recognition and SVD based least-squares fitting, and then its refined pose is estimated with a particle filtering algorithm. With real experiments, we show that the proposed method can be an effective vision- based global localization algorithm.

• Journal of Electrical Engineering and Technology
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• v.6 no.6
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• pp.806-816
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• 2011

Interest about social security has recently increased in favor of safety for infrastructure. In addition, advances in computer vision and pattern recognition research are leading to video-based surveillance systems with improved scene analysis capabilities. However, such video surveillance systems, which are controlled by human operators, cannot actively cope with dynamic and anomalous events, such as having an invader in the corporate, commercial, or public sectors. For this reason, intelligent surveillance systems are increasingly needed to provide active social security services. In this study, we propose a core technique for intelligent surveillance system that is based on swarm robot technology. We present techniques for invader enclosing using swarm robots based on multiple distributed object environment. The proposed methods are composed of three main stages: location estimation of the object, specified object tracking, and decision of the cooperative behavior of the swarm robots. By using particle filter, object tracking and location estimation procedures are performed and a specified enclosing point for the swarm robots is located on the interactive positions in their coordinate system. Furthermore, the cooperative behaviors of the swarm robots are determined via the result of path navigation based on the combination of potential field and wall-following methods. The results of each stage are combined into the swarm robot-based invader-enclosing technique on multiple distributed object environments. Finally, several simulation results are provided to further discuss and verify the accuracy and effectiveness of the proposed techniques.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.3
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• pp.91-102
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• 2004

In this paper, a fast information extraction algorithm for object-based MPEG-4 application from MPEG-1,2 is proposed. For object-based MPEG-4 conversion, we need to extract such information as object-image, shape-image, macro-block motion vector, and header information from MPEG-1,2 bit-stream. If we use the extracted information, fast conversion for object-based MPEG-4 is possible. The proposed object extraction algerian has two important steps, namely the motion vector extraction from MPEG-1,2 bit-stream and the watershed algerian The algorithm extracts objects using user's assistance in the intra frame and tracks then in the following inter frames. If we have an unsatisfactory result for a fast moving object the user can intervene to connect the segmentation. The proposed algorithm consist of two steps, which are intra frame object extracting processing and inter frame tracking processing. Object extracting process is the step in which user extracts a semantic object directly by using the block classification and watersheds. Object tracking process is the step of the following the object in the subsequent frames. It is based on the boundary fitting method using motion vector, object-mask and modified watersheds. Experimental results show that the proposed method can achieve a fast conversion from the MPEG-1,2 bit-stream to the object-based MPEG-4 input.