• Journal of Platform Technology
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• 제9권2호
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• pp.46-54
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• 2021

최근, 차량의 자율주행에 대한 기술이 개발되면서 안정성은 매우 흥미로운 요소로 관심이 증대되고 있다. 그리고 자율주행에 대하여 1980년대 중반부터 전세계의 많은 대학, 연구 센터, 자동차 회사, 그리고 다른 산업의 회사들에 의해 연구 및 개발되고 있다. 본 연구에서는 자율주행 차량의 안전성을 위한 도로의 위협적인 장애물을 자동 추출하는 방안에 대한 기초 연구를 제안한다. 자동차 도로 위에는 다양한 장애물들이 존재하지만, 본 연구에서는 위협적인 장애물은 도로의 중앙에 위치하며 비교적 큰 개체로 정의한다. 먼저, 입력 영상에 대하여 해상도를 달리하여 분할하고 분할된 영역들은 내부 영역과 외부 영역으로 분류한다. 외부 영역은 영상의 경계에 인접하고 내부 영역은 그렇지 않다. 또한, 저해상도 영상에 인접한 영역이 동일한 영역에 포함되면 각 영역은 인접 영역과 병합된다. 그리고 주요한 객체 영역과 주요한 배경 영역은 각각 내부 영역과 외부 영역에서 선택된다. 따라서, 주요한 객체 영역은 면적과 크기 정보를 활용하여 장애물을 대표하는 영역으로 추출된다. 실험을 통하여 제안된 방법이 자동차 자율주행 안전성을 높여 사고와 사상자를 줄일 수 있는 기초연구에 기여할 수 있을 것으로 기대한다.

• 제어로봇시스템학회논문지
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• 제18권4호
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• pp.321-327
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• 2012

This paper presents a comparative analysis on three different types of performance indices of obstacle detection for an overlapped ultrasonic sensor ring. Due to beam overlap, the entire sensing zone of each ultrasonic sensor can be divided into three smaller sensing subzones, which leads to significant reduction of positional uncertainty in obstacle detection. First, the positional uncertainty in obstacle detection is expressed in terms of the area of a sensing subzone, and type 1 performance index is then defined as the area ratio of side and center sensing subzones. Second, based on the area of a sensing subzone, type 2 performance index is defined taking into account the size of the entire range of obstacle detection as well as the degree of the positional uncertainty in obstacle detection. Third, the positional uncertainty in obstacle detection is now expressed in terms of the length of the uncertainty arc spanning a sensing subzone, and type 3 performance index is then defined as the average value of the uncertainty arc lengths over the entire range of obstacle detection. Fourth, using a commercial low directivity ultrasonic sensor, the changes of three different performance indices depending on the parameter of an overlapped ultrasonic sensor ring are examined and compared.

• 대한임베디드공학회논문지
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• 제10권3호
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• pp.179-188
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• 2015

We propose obstacle classification method based on 2D LIDAR(Light Detecting and Ranging) database. The existing obstacle classification method based on 2D LIDAR, has an advantage in terms of accuracy and shorter calculation time. However, it was difficult to classifier the type of obstacle and therefore accurate path planning was not possible. In order to overcome this problem, a method of classifying obstacle type based on width data of obstacle was proposed. However, width data was not sufficient to improve accuracy. In this paper, database was established by width, intensity, variance of range, variance of intensity data. The first classification was processed by the width data, and the second classification was processed by the intensity data, and the third classification was processed by the variance of range, intensity data. The classification was processed by comparing to database, and the result of obstacle classification was determined by finding the one with highest similarity values. An experiment using an actual autonomous vehicle under real environment shows that calculation time declined in comparison to 3D LIDAR and it was possible to classify obstacle using single 2D LIDAR.

• 한국응급구조학회지
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• 제20권3호
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• pp.95-105
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• 2016

Purpose: The purpose of the study was to examine the career obstacle factors and career identity according to career choice type among paramedic students. Methods: A self-reported questionnaire was completed by 234 paramedic students in C area from August 25 to September 3, 2015. The questionnaire consisted of general characteristics of the subjects, career obstacle factors, career identity, and types of career choice. The data were analyzed by t test, ANOVA, post hoc $Scheff{\acute{e}}$ test, Pearson's correlation analysis, and multiple regression analysis using SPSS v. 20.0. Results: Career obstacle factors and career identity of paramedic students had significant differences on motivation of university choice, major satisfaction, and job preference. A stable type of career choice showed a significantly lower score for career obstacle factors and a higher score for career identity. Career identity had a strongly positive relationship with major satisfaction and had a negative relationship with career obstacle factors. Logistic regression analysis revealed that the main variables affecting career identity were types of career choice, motivation of university choice, major satisfaction, and career obstacle factors. The explanatory power was 58.0%. Conclusion: The development of a career integrity enhancement program can solve the career obstacle factors for paramedic students.

• 센서학회지
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• 제16권4호
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• pp.286-293
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• 2007

For safe walking of the people who are blind, walking assistance robot which can detecting and avoiding the obstacle was investigated. The implemented prototype walking assistance robot consists of a obstacle detecting module, a user interface using acoustic signal and a driving module. The obstacle detecting module uses 6 ultrasonic sensors those located at the front part of the robot can perceive the obstacle which is in 3 meter distances and $180^{\circ}$ degrees. It calculates the distance and degree from the obstacle using TOF (time of flight) method and decides the 3-dimensional location of the obstacle. The obstacle information is delivered to the user using acoustic alarm and guide sound. The robot is designed to avoid by itself when the obstacle is detecting and the user only follows it to safe walking. After the designed robot was implemented, driving and obstacle detecting experiments were carried out. The result showed that the designed walking assistance robot will help the people who are blind to walk around safe.

• The Journal of Korean Physical Therapy
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• 제27권2호
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• pp.112-117
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• 2015

Purpose: The purpose of this study was to examine the effects of a task-specific obstacle crossing rehabilitation program on functional gait ability in patients with cerebellar ataxia. Overall, we sought to provide ataxia-specific locomotor rehabilitation guidelines for use in clinical practice based on quantitative evidence using relevant analysis of gait kinematics including valid clinical tests. Methods: Patients with cerebellar disease (n=13) participated in obstacle crossing training focusing on maintenance of dynamic balance and posture, stable transferring of body weight, and production of coordinated limb movements for 8 weeks, 2 times per week, 90 minutes per session. Throughout the training of body weight transfer, the instructions emphasized conscious perception and control of the center of body stability, trunk and limb alignment, and stepping kinematics during the practice of each walking phase. Results: According to the results, compared with pre-training data, foot clearance, pre-&post-obstacle distance, delay time, and total obstacle crossing time were increased after intervention. In addition, body COM measures indicated that body sway and movement variability, therefore posture stability during obstacle crossing, showed improvement after training. Based on these results, body sway was reduced and stepping pattern became more consistent during obstacle crossing gait after participation in patients with cerebellar ataxia. Conclusion: Findings of this study suggest that task-relevant obstacle crossing training may have a beneficial effect on recovery of functional gait ability in patients with cerebellar disease.

• 제어로봇시스템학회논문지
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• 제22권4호
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• pp.253-265
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• 2016

We propose an obstacle classification method using multi-decision factors and decision sections based on Single 2D LiDAR. The existing obstacle classification method based on single 2D LiDAR has two specific advantages: accuracy and decreased calculation time. However, it was difficult to classify obstacle type, and therefore accurate path planning was not possible. To overcome this problem, a method of classifying obstacle type based on width data was proposed. However, width data was not sufficient to enable accurate obstacle classification. The proposed algorithm of this paper involves the comparison between decision factor and decision section to classify obstacle type. Decision factor and decision section was determined using width, standard deviation of distance, average normalized intensity, and standard deviation of normalized intensity data. Experiments using a real autonomous vehicle in a real environment showed that calculation time decreased in comparison with 2D LiDAR-based method, thus demonstrating the possibility of obstacle type classification using single 2D LiDAR.

• 제어로봇시스템학회논문지
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• 제17권5호
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• pp.471-478
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• 2011

This UGV (Unmanned Ground Vehicle) is not only widely used in various practical applications but is also currently being researched in many disciplines. In particular, obstacle avoidance is considered one of the most important technologies in the navigation of an unmanned vehicle. In this paper, we introduce a simple algorithm for path planning in order to reach a destination while avoiding a polygonal-shaped static obstacle. To effectively avoid such an obstacle, a path planned near the obstacle is much shorter than a path planned far from the obstacle, on the condition that both paths guarantee that the robot will not collide with the obstacle. So, to generate a path near the obstacle, we have developed an algorithm that combines an edge detection method and a limit-cycle navigation method. The edge detection method, based on Hough Transform and IR sensors, finds an obstacle's edge, and the limit-cycle navigation method generates a path that is smooth enough to reach a detected obstacle's edge. And we proposed novel algorithm to solve local minima using the virtual wall in the local vision. Finally, we verify performances of the proposed algorithm through simulations and experiments.

• PNF and Movement
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• 제21권1호
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• pp.119-128
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• 2023

Purpose: Obstacle crossing training is being used to improve the walking ability of stroke patients, but studies on which method is more effective when performing obstacle crossing training with an unaffected limb lead (OCT-ULL) and an affected limb lead (OCT-ALL) are not well known. As such, this study aims to compare the intervention effects of obstacle crossing training using unaffected limb leads (OCT-ULL) and obstacle crossing training using affected limb leads (OCT-ALL). Methods: In total, 25 patients with chronic stroke were studied and assigned randomly to the obstacle crossing training with unaffected limb leads (OCT-ULL) group or the obstacle crossing training with affected limb leads (OCT-ALL) group. A lower extremity strength test, balance and gait test, and fall efficacy test were conducted as preliminary tests, and all patients participated in the intervention for 30 minutes a day, five days a week for four weeks, and the same preliminary tests were conducted post-intervention. Results: Compared with the OCT-ALL group, the OCT-ULL group showed a significant improvement in the strength of the affected hip abductor muscle and in balance and gait, as well as in fall efficacy (p<.05). Conclusion: This study suggested that applying the OCT-ULL training method in the obstacle crossing training of stroke patients is more effective for improving balance and gait functions than OCT-ALL.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.408-412
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• 2003

Obstacle avoidance algorithm is very important on an unmanned vehicle. Therefore, in this research, we propose a algorithm of obstacle avoidance and we can prove through vehicle test and sensor experiments. Obstacle avoidance must be divided into two parts: the first part includes the longitudinal control for acceleration and deceleration and the second part is the lateral control for steering control. Each system is used for unmanned vehicle control, which notes its location, recognizes obstacles surrounding it, and makes a decision how fast to proceed according to circumstances. During the operation, the control strategy of the vehicle can detect obstacles and perform obstacle avoidance on the road, which involves vehicle velocity. In this paper, we propose a method for vehicle control, modeling, and obstacle avoidance, which are confirmed through vehicle tests.