• Journal of KIISE:Software and Applications
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• v.37 no.8
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• pp.641-646
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• 2010

This paper presents algorithms for real-time navigation of a humanoid robot with a stereo vision but no other sensors. Using the algorithms, a robot can recognize its 3D environment by retrieving SIFT features from images, estimate its position through the Kalman filter, and plan its path to reach a destination avoiding obstacles. Our approach focuses on estimating the robot’s central walking path trajectory rather than its actual walking motion by using an approximate model. This strategy makes it possible to apply mobile robot localization approaches to humanoid robot localization. Simple collision free path planning and motion control enable the autonomous robot navigation. Experimental results demonstrate the feasibility of our approach.

• International journal of advanced smart convergence
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• v.5 no.4
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• pp.21-25
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• 2016

Recent development in multi-channel surround is emerging in various formats to provide better stereoscopic and sound effects to consumers in recent broadcasting. The ability sound localize the sound sources in space is most considerable design factor on multi-channel surround system for human earing perception model. However, this paper propose the change of the sound localization according to the spacing of the speakers, which is not covered in the existing research focus on sound system design. Presently the sound system uses the position and number of the speakers to localize the sound. In the multi-channel surround environment, the proposed design uses the sound localization is caused by the directional characteristics of the speaker, the distance between the speakers and the distance between the listener and the speaker according to the directivity is required. The proposed design is simulated using virtual measurement with MATLAB simulation environment and performances are measured.

• Journal of Broadcast Engineering
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• v.16 no.5
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• pp.846-860
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• 2011

The binaural auditory system of human has ability to differentiate the direction and the distance of the sound sources by using the information which are inter-aural intensity difference(IID), inter-aural time difference(ITD) and/or the spectral shape difference(SSD). These information is generated from the acoustical transfer of a sound source to pinna, the outer ears. We can create a virtual sound system using the information which is called Head related transfer function(HRTF). However the performance of 3D sound is not always satisfactory because of non-individual characteristics of the HRTF. In this paper, we propose the algorithm that uses human's auditory characteristics for accurate perception. To achieve this, excitation energy of HRTF, global masking threshold and loudness are applied to the proposed algorithm. Informal listening test shows that the proposed method improves the sound localization characteristics much better than conventional methods.

• Spatial Information Research
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• v.21 no.1
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• pp.45-52
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• 2013

Recently 3D surveying is recommended to manage underground facilities systematically before refilling of site operation. As the demand of realtime localization increases, cost reduction and consistent data construction which are realizable by using one man surveying method with unmanned target, are necessary for constructing DB of all sorts of the underground facilities with more speediness and correctness. This study sets a goal to develop a new type of surveying target which allows realtime localization to be performed by one man, through making an optimum reflector(triangle, quadrangle, and semispherical shape) by using the retro-reflection principle of optical prism which is being used for surveying currently. The new surveying target makes realtime surveying possible. To check reliability of its data, the accuracy is compared with surveying coordination of total station for each type in a quantitative method. In the result, the usefulness of the reflector for Underground Facilities localization is proved. Thus the foundation for underground DB construction conducted by one man is established for acquisition of 3D location information in more efficient way through using unmanned target.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.2
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• pp.116-124
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• 2011

A service robot can identify its own position relative to landmarks, the locations of which are known in advance. The main contribution of this research is that it gives various ways of making the self-localizing error smaller by referring to special landmarks which are developed as high gain reflection material and coded array associations. In this paper, the authors propose a set of indices to evaluate the accuracy of self-localizing methods using the selective reflection landmark and infrared projector, and the indices are derived from the sensitivity enhancement using 3D distortion calibration of camera. And then, the accurarcy of self-localizing a mobile robot with landmarks based on the indices is evaluated, and a rational way to minimize to reduce the computational cost of selecting the best self-localizing method. The simulation results show a high accuracy and a good performance.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2011.10a
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• pp.717-722
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• 2011

In this paper, noise source localization of the Korean high speed train was conducted by using delay and sum beam-forming method of a microphone array. At first, the microphone array having irregular configuration was designed and the resolution of which was analyzed from parameters such as 3-dB bandwidth and maximum side-lobe level. After the demonstration, the microphone array was applied on the high speed train and noise localization of the high speed train driving at 300 km/h was performed successfully.

• The Journal of Korea Robotics Society
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• v.19 no.2
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• pp.149-158
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• 2024

This paper presents a robust autonomous navigation and reconnaissance system for tracked robots, designed to handle complex multi-floor indoor environments with stairs. We introduce a localization algorithm that adjusts scan matching parameters to robustly estimate positions and create maps in environments with scarce features, such as narrow rooms and staircases. Our system also features a path planning algorithm that calculates distance costs from surrounding obstacles, integrated with a specialized PID controller tuned to the robot's differential kinematics for collision-free navigation in confined spaces. The perception module leverages multi-image fusion and camera-LiDAR fusion to accurately detect and map the 3D positions of objects around the robot in real time. Through practical tests in real settings, we have verified that our system performs reliably. Based on this reliability, we expect that our research team's autonomous reconnaissance system will be practically utilized in actual disaster situations and environments that are difficult for humans to access, thereby making a significant contribution.

• International Journal of Precision Engineering and Manufacturing
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• v.6 no.4
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• pp.60-66
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• 2005

In this paper, we propose the basic measurement method of a 3D digitizer using a CCD camera in detail. In the localization measurement with a CCD camera, the effect of the background light and the sensitivity consideration are always problems in realizing a high precision. In this research, a new measurement principle is proposed in which the pulse compression technique known in radar is used to eliminate the effect of background light even under a low intensity light source, and the coordinate values on the CCD camera image plane are determined accurately. From the quantitative evaluation of the S/N ratio improvement and the fundamental experiment, it is verified that a substantial improvement in the S/N ratio is realized for both the background noise and the pixel noise and that a resolution of less than the pixel is sufficiently possible.

• Journal of Life Science
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• v.27 no.7
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• pp.849-856
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• 2017

The ${\beta}$-D-fructofuranosidase (EC 3.2.1.26) is an important enzyme from a historical point of view, discovered by French biologist Berthelot in 1860 and was first used to study enzymology. ${\beta}$-D-fructosfuranosidase catalyzes the hydrolysis of sucrose into D-glucose and D-fructose. Four biochemical subgroups of ${\beta}$-D-fructofuranosidase have been investigated in plants. There are vacuolar (soluble acid), cytoplasmic (soluble alkaline), membrane-bound (insoluble alkaline), and cell wall-bound (insoluble acid) ${\beta}$-D-fructofuranosidase by purification. Their biochemical characteristics are distinct. It suggested that those enzymes might be different gene products. The contribution of each of these enzymes to sucrose management in the plant is likely to be correlated with their localization. Common localization in developing cells in tissues from a range of developmental stages and plant parts suggests that all of the isoforms may be closely involved in nutrient transport. The ${\beta}$-D-fructofuranosidases were most commonly found associated with maturing tissues in developing fruits, leaves, and roots. The ${\beta}$-D-fructofuranosidase activity varies in the relationship between growth and expansion through cell division, development of storage organs and tissues, and the relationship of plant defense responses. It is necessary to summarize more researches in order to know the definite physiological function.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.45 no.6
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• pp.49-59
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• 2008

SIFT(Scale Invariant Feature Transform) is an algorithm to extract vectors at pixels around keypoints, in which the pixel colors are very different from neighbors, such as vortices and edges of an object. The SIFT algorithm is being actively researched for various image processing applications including 3-D image constructions, and its most computation-intensive stage is a keypoint localization. In this paper, we develope a fixed-point model of the keypoint localization and propose its efficient hardware architecture for embedded applications. The bit-length of key variables are determined based on two performance measures: localization accuracy and error rate. Comparing with the original algorithm (implemented in Matlab), the accuracy and error rate of the proposed fixed point model are 93.57% and 2.72% respectively. In addition, we found that most of missing keypoints appeared at the edges of an object which are not very important in the case of keypoints matching. We estimate that the hardware implementation will give processing speed of $10{\sim}15\;frame/sec$, while its fixed point implementation on Pentium Core2Duo (2.13 GHz) and ARM9 (400 MHz) takes 10 seconds and one hour each to process a frame.