• Journal of Institute of Control, Robotics and Systems
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• v.15 no.2
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• pp.155-162
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• 2009

In walking guide robot, a guide vehicle detects an obstacle distribution in the walking space using range sensors, and generates a 3D grid map to map the obstacle information and the tactile display. And the obstacle information is transferred to a blind pedestrian using tactile feedback. Based on the obstacle information a user plans a walking route and controls the guide vehicle. The algorithm for 3D detection of an obstacle distribution and the method of mapping the generated obstacle map and the tactile display device are proposed in this paper. The experiment for the 3D detection of an obstacle distribution using ultrasonic sensors is performed and estimated. The experimental system consisted of ultrasonic sensors and control system. In the experiment, the detection of fixed obstacles on the ground, the moving obstacle, and the detection of down-step are performed. The performance for the 3D detection of an obstacle distribution and space mapping is verified through the experiment.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.7
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• pp.552-556
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• 2016

Obstacle detection is a key feature in the safe driving control of electric wheelchairs. The suggested obstacle detection algorithm was designed to provide obstacle avoidance direction and detect the existence of cliffs. By means of this information, the wheelchair can determine where to steer and whether to stop or go. A 3D depth camera (Microsoft KINECT) is used to scan the 3D point data of the scene, extract information on obstacles, and produce a steering direction for obstacle avoidance. To be specific, ground detection is applied to extract the obstacle candidates from the scanned data and the candidates are projected onto a 2D map. The 2D map provides discretized information of the extracted obstacles to decide on the avoidance direction (left or right) of the wheelchair. As an additional function, cliff detection is developed. By defining the "cliffband," the ratio of the predefined band area and the detected area within the band area, the cliff detection algorithm can decide if a cliff is in front of the wheelchair. Vehicle tests were carried out by applying the algorithm to the electric wheelchair. Additionally, detailed functions of obstacle detection, such as providing avoidance direction and detecting the existence of cliffs, were demonstrated.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.8
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• pp.783-789
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• 2007

In this paper, firstly, we propose a generating method of the 3-D obstacle map using ultrasonic sensors. Secondly, we try to find the necessary stimulation conditions of compact tactile display device for effective transfer of obstacle information. The final goal of this research is the development of a walking guide system for the blind to walk safely. The walking guide system consists of a guide vehicle for the obstacle detection and a tactile display device for the transfer of the obstacle information. The guide vehicle, located in front of the walking blind, detects the obstacle using ultrasonic sensors. The processed information makes an obstacle map and transmits safe path and emergency situation to the blind by the tactile display. 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 concept of a walking guide system with tactile display is introduced, and experiments of 3-D obstacle detection and tactile perception are carried out and analyzed.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.5
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• pp.419-428
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• 2011

This paper suggests a judgement method for an inclined plane before entrance of it and the detection of obstacle position. Main idea is started from the assumption that obstacle is always on the bottom plane, and corner appears at this position. The process to detect the obstacle consists of three steps. First the 3D data using stereo matching is acquired to detect an obstacle. Second a bottom plane is extracted by using limit condition. Last the obstacle position is found by using Harris corner detection. Obstacle position detection on an inclined plane was verified by outdoor and indoor experiment. In error analysis, it is confirmed that an average error of obstacle detection in outdoor was larger than the error in indoor but the error are within about 0.030 m. This method will be applied to unmanned vehicles to navigate under various environment.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.43 no.3 s.309
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• pp.8-15
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• 2006

Obstacle detection is an important task for many mobile robot applications. The methods using stereo vision and optical flow are computationally expensive. Therefore, this paper presents a vision-based obstacle detection method using only two view images. The method uses a single passive camera and odometry, performs in real-time. The proposed method is an obstacle detection method using 3D reconstruction from taro views. Processing begins with feature extraction for each input image using Dr. Lowe's SIFT(Scale Invariant Feature Transform) and establish the correspondence of features across input images. Using extrinsic camera rotation and translation matrix which is provided by odometry, we could calculate the 3D position of these corresponding points by triangulation. The results of triangulation are partial 3D reconstruction for obstacles. The proposed method has been tested successfully on an indoor mobile robot and is able to detect obstacles at 75msec.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.2
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• pp.342-348
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• 2016

We propose an obstacle detection algorithm for unmanned ground vehicle on uneven terrain. The key ideas of the proposed algorithm are the use of two-layer laser range data to calculate the gradient of a target, which is characterized as either ground or obstacles. The proposed obstacle detection algorithm includes 4-steps: 1) Obtain the distance data for each angle from multiple lidars or a multi-layer scan lidar. 2) Calcualate the gradient for each angle of the uneven terrain. 3) Determine ground or obstacle for each angle on the basis of reference gradient. 4) Generate a new distance data for each angle for a virtual laser scanner. The proposed algorithm is verified by various experiments.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.3D
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• pp.367-374
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• 2006

This research revealed the operation problems of the current crossing control systems through inspecting and testing the obstacle detection systems and gate control systems for the crossings. To resolve the problems of the crossing control systems, this research developed new algorithms of four-quadrant gate system and obstacle detection systems combing the functions of rasar sensors and magnetic sensors and tested the reliability of the systems. Currently, the obstacle detection systems and gate control systems controls approaching and departing traffic by simply detecting vehicles and obstacles but do not consider traffic movements at the crossings. In addition, they do not make signal cooperation for gate controls. As a result, such inefficient crossing controls result in unsafe gate controls for drivers. Therefore, the newly developed crossing control systems through this study will provide more effective crossing control services with more strengthen information cooperation within control systems. Besides they will help to reduce train crashes at the crossings by gate control systems considering various driving behaviors.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.3
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• pp.323-328
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• 2011

In real system application, the 3-D obstacle avoidance system for the autonomous control of the underwater flight vehicle (UFV) operates with the following problems: the sonar offers the range/bearing information of obstacles in a local detection area, it requires the system that has reduced acoustic noise and power consumption in terms of the autonomous underwater vehicle (AUV), it has the UFV operation constraints such as maximum pitch and depth, and it requires an easy design procedure in terms of its structures and parameters. To solve these problems, an intelligent 3-D obstacle avoidance algorithm using the evolution strategy (ES) and the fuzzy logic controller (FLC), is proposed. To verify the performance of the proposed algorithm, the 3-D obstacle avoidance of UFV is performed. Simulation results show that the proposed algorithm effectively solves the problems in the real system application.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2009.04a
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• pp.244-245
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• 2009

일반적으로 LiDAR(Light Detection And Ranging)의 자료로부터 3차원 위치정보와 속성 정보를 취득하여 활용 하는 연구가 많이 진행되고 있다. 본 연구에서는 Grid($100m{\times}100m$) 기반인 2차원적 Grid Point를 통해 Sensor Field를 정하고 LiDAR의 3차원적 좌표정보를 이용하여 최적 센서 위치를 선정하고 중간에 장애물(Obstacle)이 존재하는 경우 또한 알고리즘을 통해 최적위치인 Grid point를 선정하였다. 알고리즘은 3가지 측면을 고려하여 분류하였다. 첫째 장애물이 없는(Non Obstacle) 2차원적인 경우, 둘째 장애물이 존재(Obstacle)하는 2차원적인 경우, 셋째 장애물이 존재(Obstacle)하며 3차원적인 알고리즘을 고려하였다. 향후 연구에서는 LiDAR를 직접 적용하여 최적 선정 지역을 도출하여 알고리즘을 적용할 것이다.

• Advances in robotics research
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• v.1 no.2
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• pp.127-140
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• 2014

This work presents an IR-based system for parking assistance and obstacle detection in the automotive field that employs the Microsoft Kinect camera for fast 3D point cloud reconstruction. In contrast to previous research that attempts to explicitly identify obstacles, the proposed system aims to detect "reachable regions" of the environment, i.e., those regions where the vehicle can drive to from its current position. A user-friendly 2D traversability grid of cells is generated and used as a visual aid for parking assistance. Given a raw 3D point cloud, first each point is mapped into individual cells, then, the elevation information is used within a graph-based algorithm to label a given cell as traversable or non-traversable. Following this rationale, positive and negative obstacles, as well as unknown regions can be implicitly detected. Additionally, no flat-world assumption is required. Experimental results, obtained from the system in typical parking scenarios, are presented showing its effectiveness for scene interpretation and detection of several types of obstacle.