• Agricultural and Biosystems Engineering
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• v.2 no.2
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• pp.69-74
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• 2001

Detection of operation lines in farm works, object recognition and obstacle avoidance are essential pre-requisite technologies for unmanned agricultural machinery. A CCD camera, which has been largely used for these functions, is expensive and has difficulty in real-time signal processing. In this study, a laser range sensor was selected as the guiding vision for unmanned agricultural machinery such as a tractor. To achieve this capability, algorithms for distance measurement, signal filtering, object recognition, and obstacle avoidance were developed. Computer simulations were carried out to evaluate performance of the algorithms. Experiments were also conducted with various materials and shapes, Laser beam lost its intensity for poor reflective materials, resulting in less range value than actual, so a compensation technique was considered to be necessary. Object detection system was fabricated on an agricultural tractor and the performance was evaluated. As test result for obstacle detection and avoidance in field, to detect and avoid obstacle for path finding with guiding system for unmanned agricultural machinery was enable.

• Journal of the Korean Society of Industry Convergence
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• v.22 no.2
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• pp.209-218
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• 2019

This study proposes a new approach to Control the Orientation and position based on obstacle avoidance technology by multi sensors fusion and autonomous travelling control of mobile robot system for implimentation of Smart FA. The important focus is to control mobile robot based on by the multiple sensor module for autonomous travelling and obstacle avoidance of proposed mobile robot system, and the multiple sensor module is consit with sonar sensors, psd sensors, color recognition sensors, and position recognition sensors. Especially, it is proposed two points for the real time implementation of autonomous travelling control of mobile robot in limited manufacturing environments. One is on the development of the travelling trajectory control algorithm which obtain accurate and fast in considering any constraints. such as uncertain nonlinear dynamic effects. The other is on the real time implementation of obstacle avoidance and autonomous travelling control of mobile robot based on multiple sensors. The reliability of this study has been illustrated by the computer simulation and experiments for autonomous travelling control and obstacle avoidance.

• Journal of Auto-vehicle Safety Association
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• v.11 no.2
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• pp.35-43
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• 2019

This paper describes the improved environment recognition algorithms using some type of sensors like LiDAR and cameras. Additionally, integrated control algorithm for an autonomous vehicle is included. The integrated algorithm was based on C++ environment and supported the stability of the whole driving control algorithms. As to the improved vision algorithms, lane tracing and traffic sign recognition were mainly operated with three cameras. There are two algorithms developed for lane tracing, Improved Lane Tracing (ILT) and Histogram Extension (HIX). Two independent algorithms were combined into one algorithm - Enhanced Lane Tracing with Histogram Extension (ELIX). As for the enhanced traffic sign recognition algorithm, integrated Mutual Validation Procedure (MVP) by using three algorithms - Cascade, Reinforced DSIFT SVM and YOLO was developed. Comparing to the results for those, it is convincing that the precision of traffic sign recognition is substantially increased. With the LiDAR sensor, static and dynamic obstacle detection and obstacle avoidance algorithms were focused. Therefore, improved environment recognition algorithms, which are higher accuracy and faster processing speed than ones of the previous algorithms, were proposed. Moreover, by optimizing with integrated control algorithm, the memory issue of irregular system shutdown was prevented. Therefore, the maneuvering stability of the autonomous vehicle in severe environment were enhanced.

• The Journal of the Convergence on Culture Technology
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• v.8 no.5
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• pp.219-228
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• 2022

The purpose of this study is to explore what obstacles adult undergraduate experience in adapting to college life. To this end, in-depth interviews were conducted with 32 adult undergraduate attending colleges in Daegu and Gyeongbuk. For the study, Colaizzi's phenomenological research method was used and analyzed. As a result of the analysis, eight factors such as relation obstacle, bachelor's and curriculum operation obstacle, social recognition obstacle, study ability obstacle, college environment obstacle, economic obstacle, personal disposition obstacle, and temporal obstacle were found. Through the above research results, it was found that the college environment, which is operated mainly by general college students, is expressed as various types of obstacle for adult undergraduate who work and study at various ages and experiences. Based on the derived obstacle factors, it is expected that a follow-up study will be conducted to develop a measurement tool that can empirically explore the obstacle of adult undergraduate to adapt to college life.

• Journal of Broadcast Engineering
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• v.22 no.6
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• pp.724-733
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• 2017

Conventional methods of automatically recording Go game positions do not properly consider obstacles (hand or object) on a Go board during the Go game. If the Go board is blocked by obstacles, the position of a Go stone may not be correctly recognized, or the sequences of moves may be stored differently from the actual one. In the proposed algorithm, only the complete Go board image without obstacles is stored as a background image and the obstacle is recognized by comparing the background image with the current input image. To eliminate the phenomenon that the shadow is mistaken as obstacles, this paper proposes the new obstacle detection method based on the gradient image instead of the simple differential image. When there is no obstacle on the Go board, the background image is updated. Finally, the successive background images are compared to recognize the position and type of the Go stone. Experimental results show that the proposed algorithm has more than 95% recognition rate in general illumination environment.

• Proceedings of the KIEE Conference
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• 1995.11a
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• pp.587-589
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• 1995

The safe navigation of a mobile robot requires the recognition of the environment in terms of vision processing. To be guided in the given path, the robot should acquire the information about where the wall and corridor are located. Also unexpected obstacles should be detected as rapid as possible for the safe obstacle avoidance. In the paper, we assume that the mobile robot should be navigated in the flat surface. In terms of this assumption we simplify the correspondence problem by the free navigation surface and matching features in that coordinate system. Basically, the vision processing system adopts line segment of edge as the feature. The extracted line segments of edge out of both image are matched in the free nevigation surface. According to the matching result, each line segment is labeled by the attributes regarding obstacle and free surface and the 3D shape of obstacle is interpreted. This proposed vision processing method is verified in terms of various simulations and experimentation using real images.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2381-2383
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• 2003

This paper presents an effective approach to dynamic obstacle avoidance for mobile robot. The main concept of this approach includes modified polar mapping for recognition of the moving obstacle in vision-based robot systems. To simplify the segmentation of the moving obstacle from the background and to obtain its relative position data the modified polar mapping is proposed. Dynamic moving obstacles are avoided with a vision sensor and stationary obstacles are avoided with a sonar sensor.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.888-891
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• 2005

In this paper, the prototype of a walking guide robot with tactile display is introduced, and the psychophysical experiment of the tactile recognition for a tactile display is carried out and analyzed. The objective of this research is the development of a walking guide robot for the blind to walk safely. A walking guide robot consists of a guide vehicle and a tactile display device. A guide vehicle, located in the front of the walking blind, detects the obstacle using ultrasonic sensors and offers the information of position and walking direction acquired from GPS module to the walking blind by voice. The tactile display device, located in the handle which is connected with the guide vehicle by cane, offers the processed obstacle information such as position, size, moving, shape of obstacle and safe path, etc. The psychophysical experiments for the threshold of perception and recognition ability of tactile stimulation are carried out by the estimation of the subject group. As a result the appropriate tactile stimulus intensity and frequency to recognize tactile stimulation effectively are discussed and derived.

• Journal of the Korean Society of Industry Convergence
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• v.17 no.2
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• pp.42-53
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• 2014

Robust voice recognition (RVR) is essential for a robot to communicate with people. One of the main problems with RVR for robots is that robots inevitably real environment noises. The noise is captured with strong power by the microphones, because the noise sources are closed to the microphones. The signal-to-noise ratio of input voice becomes quite low. However, it is possible to estimate the noise by using information on the robot's own motions and postures, because a type of motion/gesture produces almost the same pattern of noise every time it is performed. In this paper, we propose an RVR system which can robustly recognize voice by adults and children in noisy environments. We evaluate the RVR system in a communication robot placed in a real noisy environment. Voice is captured using a wireless microphone. Navigation Strategy is shown Obstacle detection and local map, Design of Goal-seeking Behavior and Avoidance Behavior, Fuzzy Decision Maker and Lower level controller. The final hypothesis is selected based on posterior probability. We then select the task in the motion task library. In the motion control, we also integrate the obstacle avoidance control using ultrasonic sensors. Those are powerful for detecting obstacle with simple algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1408-1412
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• 2004

This paper presents a method that a mobile robot finds location of doors in complex environments and safely traverses the door. A robot must be able to find the door in order that it achieves the behavior that is scheduled after traversing a door. PCA(Principal Component Analysis) algorithm using the vision sensor is used for a robot to find the location of door. Fuzzy controller using sonar data is used for a robot to avoid an obstacle and traverse the doors.