• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.8
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• pp.1605-1614
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• 2009

The technique of simultaneous localization and mapping is the most important research topic in mobile robotics. In the process of building a map in its available memory, the robot memorizes environmental information on the plane of grid or topology. Several approaches about this technique have been presented so far, but most of them use mapping technique as either grid-based map or topology-based map. In this paper we propose a frame of solving the SLAM problem of linking map covering, map building, localizing, path finding and obstacle avoiding in an automatic way. Some algorithms integrating grid and topology map are considered and this make the SLAM performance faster and more stable. The proposed scheme uses an occupancy grid map in representing the environment and then formulate topological information in path finding by A${\ast}$ algorithm. The mapping process is shown and the shortest path is decided on grid based map. Then topological information such as direction, distance is calculated on simulator program then transmitted to robot hardware devices. The localization process and the dynamic obstacle avoidance can be accomplished by topological information on grid map. While mapping and moving, pose of the robot is adjusted for correct localization by implementing additional pixel based image layer and tracking some features. A laser range finer and electronic compass systems are implemented on the mobile robot and DC geared motor wheels are individually controlled by the adaptive PD control method. Simulations and experimental results show its performance and efficiency of the proposed scheme are increased.

• ETRI Journal
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• v.42 no.5
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• pp.748-760
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• 2020

MapReduce is a framework that can process huge datasets in parallel and distributed computing environments. However, a single machine failure during the runtime of MapReduce tasks can increase completion time by 50%. MapReduce handles task failures by restarting the failed task and re-computing all input data from scratch, regardless of how much data had already been processed. To solve this issue, we need the computed key-value pairs to persist in a storage system to avoid re-computing them during the restarting process. In this paper, the task failure resilience (TFR) technique is proposed, which allows the execution of a failed task to continue from the point it was interrupted without having to redo all the work. Amazon ElastiCache for Redis is used as a non-volatile cache for the key-value pairs. We measured the performance of TFR by running different Hadoop benchmarking suites. TFR was implemented using the Hadoop software framework, and the experimental results showed significant performance improvements when compared with the performance of the default Hadoop implementation.

• Journal of Korea Multimedia Society
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• v.6 no.1
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• pp.176-182
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• 2003

The use of the A* for the path search of the agent in the game map gives the computational overhead in real time game processing. To solve this problem, the route table was presented for the 2D game This route table is made in the game development phase and utilized in game playing. The route table designed for 2D game is extended for 3D game in this paper. But the memory space is required too much. This Problem can also be solved using the data compression by skipping the duplicated route table.

• Journal of Internet Computing and Services
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• v.3 no.6
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• pp.35-41
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• 2002

The Car Navigation System(CNS) requires lots of memory and calculating time because it works on the large and complex digital map. And the traffic circumstances vary time by time, so the traffic informations should be processed if we want to get mere realistic result. This paper proposes an effective path searching algorithm which uses less memories and calculating time by applying directional information between the starting place and destination place and by using realtime traffic informations.

• The Transactions of the Korea Information Processing Society
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• v.7 no.5
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• pp.1570-1578
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• 2000

Object motion is an important feature of content in video sequences. By now, various methods to exact feature about the object motion have been reported[1,2]. However they are not suitable to index video using the motion, since a lot of bits and complex indexing parameters are needed for the indexing [3,4] In this paper, we propose object motion map which could provide efficient indexing method for object motion. The proposed object motion map has both global and local motion information during an object is moving. Furthermore, it requires small bit of memory for the indexing. to evaluate performance of proposed indexing technique, experiments are performed with video database consisting of MPEG-1 video sequence in MPEG-7 test set.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.6B
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• pp.1183-1190
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• 1999

This paper presents an efficient hardware architecture to improve the frame memory interface occupying the largest hardware area together with motion estimator in implementing MPEG-2 video encoder as an ASIC chip. In this architecture, the memory size for internal data buffering and hardware area for frame memory interface control logic are reduced through the efficient memory map organization of the external SDRAM having dual bank and memory access timing optimization between the video encoder and external SDRAM. In this design, 0.5 m, CMOS, TLM (Triple Layer Metal) standard cells are used as design libraries and VHDL simulator and logic synthesis tools are used for hardware design add verification. The hardware emulator modeled by C-language is exploited for various test vector generation and functional verification. The architecture of the improved frame memory interface occupies about 58% less hardware area than the existing architecture[2-3], and it results in the total hardware area reduction up to 24.3%. Thus, the (act that the frame memory interface influences on the whole area of the video encoder severely is presented as a result.

• Journal of Sensor Science and Technology
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• v.7 no.2
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• pp.124-130
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• 1998

High-speed 3D vision systems are essential for autonomous robot or vehicle control applications. In our study, a stereo vision process has been developed. It consists of three steps : extraction of edges in right and left images, matching corresponding edges and calculation of the 3D map. This process is implemented in a VME 150/40 Imaging Technology vision system. It is a modular system composed by a display, an acquisition, a four Mbytes image frame memory, and three computational cards. Programmable accelerator computational modules are running at 40 MHz and are based on TMS320C31 DSP with a $64{\times}32$ bit instruction cache and two $1024{\times}32$ bit internal RAMs. Each is equipped with 512 Kbytes static RAM, 4 Mbytes image memory, 1 Mbytes flash EEPROM and a serial port. Data transfers and communications between modules are provided by three 8 bit global video bus, and three local configurable pipeline 8 bit video bus. The VME bus is dedicated to system management. Tasks between DSPs are distributed as follows: two DSPs are used to edges detection, one for the right image and the other for the left one. The last processor computes the matching process and the 3D calculation. With $512{\times}512$ pixels images, this sensor generates dense 3D maps at a rate of about 1 Hz depending of the scene complexity. Results can surely be improved by using a special suited multiprocessors cards.

• The KIPS Transactions:PartD
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• v.10D no.3
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• pp.359-366
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• 2003

Although the reuse of the cached data for scrolling the map reduces the amount of passed data between client and server, it needs the conversions of data coordinates, selective deletion of objects, cache compaction and object structuring step in the clients. The conversion is a time- intensive operation due to limited resources of mobile phones such as low computing power, small memory. Therefore, in order to control the map efficiently in the vector map service based mobile phones, it is necessary to study the methods which reuse cached objects for reducing wireless network bandwidth and overwhelming the limited resources of mobile phones as well. This paper proposes the methods of reusing pre-received spatial objects for map control in the mobile vector map service system based on client-server architecture. The experiments conducted on the Web GIS systems with real data show that the proposed method is appropriate to map services for mobile phone. We also analyze the advantages and drawbacks between the reuse of cached data and transmission of raw data respectively.

• Journal of Convergence for Information Technology
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• v.12 no.1
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• pp.7-14
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• 2022

Unlike general maps, the underground geospatial Information is a system made to view underground information in a 3D shape. This system is managed by a tile maps to lighten the data. But there are various underground structures in the basement, and the structures are made of 3D data, so the data size is large. Therefore, when a client mobile program requests a tile map, the service server fetches the requested tile map from the DB server and transmits ti to the client, but there is a transmission delay time problem. In this paper, we design the tile cache method to improve the request response speed for the tile map data provided to the client in the mobile underground geospatial information system. We propose a method in which a service server predicts and prefetchs the next tile map while the client is viewing tile map, and stores the prefetching data in the memory of client mobile terminal. Then, the transmission delay time problem can be solved.

• International Journal of Computer Science & Network Security
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• v.23 no.3
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• pp.177-186
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• 2023

Hyperspectral imaging technology is one of the most efficient and fast-growing technologies in recent years. Hyperspectral image (HSI) comprises contiguous spectral bands for every pixel that is used to detect the object with significant accuracy and details. HSI contains high dimensionality of spectral information which is not easy to classify every pixel. To confront the problem, we propose a novel RGB channel Assimilation for classification methods. The color features are extracted by using chromaticity computation. Additionally, this work discusses the classification of hyperspectral image based on Domain Transform Interpolated Convolution Filter (DTICF) and 3D-CNN with Bi-directional-Long Short Term Memory (Bi-LSTM). There are three steps for the proposed techniques: First, HSI data is converted to RGB images with spatial features. Before using the DTICF, the RGB images of HSI and patch of the input image from raw HSI are integrated. Afterward, the pair features of spectral and spatial are excerpted using DTICF from integrated HSI. Those obtained spatial and spectral features are finally given into the designed 3D-CNN with Bi-LSTM framework. In the second step, the excerpted color features are classified by 2D-CNN. The probabilistic classification map of 3D-CNN-Bi-LSTM, and 2D-CNN are fused. In the last step, additionally, Markov Random Field (MRF) is utilized for improving the fused probabilistic classification map efficiently. Based on the experimental results, two different hyperspectral images prove that novel RGB channel assimilation of DTICF-3D-CNN-Bi-LSTM approach is more important and provides good classification results compared to other classification approaches.