• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.6
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• pp.599-607
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• 2021

Street-view images, which are omnidirectional scenes centered on a specific location on the road, can provide various obstacle information for the pedestrians. Pedestrian network data for the navigation services should reflect the up-to-date obstacle information to ensure the mobility of pedestrians, including people with disabilities. In this study, the object detection model was trained for the bollard as a major obstacle in Seoul using street-view images and a deep learning algorithm. Also, a process for updating information about the presence and number of bollards as obstacle properties for the crosswalk node through spatial matching between the detected bollards and the pedestrian nodes was proposed. The missing crosswalk information can also be updated concurrently by the proposed process. The proposed approach is appropriate for crowdsourcing data as the model trained using the street-view images can be applied to photos taken with a smartphone while walking. Through additional training with various obstacles captured in the street-view images, it is expected to enable efficient information update about obstacles on the road.

• Journal of the Korea Society of Computer and Information
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• v.18 no.2
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• pp.117-126
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• 2013

Path planning is an essential problem to make virtual characters navigate in many applications including computer games. In many cases, multiple characters move in a group and qualitative aspects of planned paths are emphasized rather than optimality unlike Robotics. In this paper, we propose a two-level path planning algorithm in which the global path is planned for a single character specified as a leader and then the local path is planned to avoid dynamic obstacles while the group following this path. The space for group movement is achieved in the form of square grid array called a grid window. Member characters are located relatively to the leader within a space and moved. The static environment is reduced to the configuration space of this grid window to generate a roadmap on which a grid window can move. In local path planning, only the leader avoids dynamic obstacles by using an artificial potential field and the rest of members are located relatively to the leader in the grid window, which reduces computational load. Efficient algorithms to implement the proposed planning methods are introduced. The simulation results show that a group can handle with dynamic obstacles effectively while moving along the planned path for a static environment.

• Journal of the Institute of Convergence Signal Processing
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• v.12 no.4
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• pp.341-347
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• 2011

This paper presents the performance evaluation. optimal design. and complex obstacle detection of an overlapped ultrasonic sensor ring by introducing a new concept of effective beam width. It is assumed that a set of ultrasonic sensors of the same type are arranged along a circle of nonzero radius at regular spacings with their beams overlapped. First, the global positional uncertainty of an overlapped ultrasonic sensor ring is expressed by the average value of local positional uncertainty over the entire obstacle detection range. The effective beam width of an overlapped ultrasonic sensor ring is assessed as the beam width of a single ultrasonic sensor having the same amount of global positional uncertainty, from which a normalized obstacle detection performance index is defined. Second. using the defined index, the design parameters of an overlapped ultrasonic sensor ring are optimized for minimal positional uncertainty in obstacle detection. For a given number of ultrasonic sensors, the optimal radius of an overlapped ultrasonic sensor ring is determined, and for a given radius of an overlapped ultrasonic sensor ring, the optimal number of ultrasonic sensors is determined. Third, the decision rules of positional uncertainty zone for multiple obstacle detection are provided based on the inequality relationships among obstacle distances by three adjacent ultrasonic sensors. Using the provided rules, the obstacle outline detection is performed in a rather complex environment consisting of several obstacles of different shapes.

• The Journal of the Korea Contents Association
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• v.19 no.3
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• pp.72-79
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• 2019

Autonomous locomotion has two essential functionalities: mapping builds and updates maps by uncertain position information and measured sensor inputs, and localization is to find the positional information with the inaccurate map and the sensor information. In addition, obstacle detection, avoidance, and path designs are necessarily required for autonomous locomotion by combining the probabilistic methods based on uncertain locations. The sensory inputs, which are measured by a metric-based scanner, have difficulties of distinguishing moving obstacles like humans from static objects like walls in given environments. This paper proposes the low resolution grid map combined with reinforcement learning, which is compared with the conventional recognition method for detecting static and moving objects to generate obstacle avoiding path. Finally, the proposed method is verified with experimental results.

• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.353-356
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• 2003

본 논문은 이동로봇의 다양한 작업들 중에 선행하는 물체를 안정하게 추종하는 동작중 예기치 못한 움직이는 장애물의 효과적인 회피 방법을 고려한다. 센서 기반의 이동로보트에서는 이동물체 추종과 충돌회피를 센서정보에 의존해서 해결해야 하는데 동일한 센서 정보로 추종물체와 충돌물체를 구분하는 것이 쉽지 않은 문제이다. 또한 명확히 규정되지 않은 환경에서 적용하기 어렵다. 따라서 본 논문에서는 이와 같이 명확히 규정되지 않은 환경에서 선행물체의 안정한 추종과 추종 중에 마주치는 이동 장애물에 대한 충돌회피를 위하여 이동로봇의 상태 판단에 따라 구분된 행동 선택 모드를 제안하고 실험적으로 확인한다.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.43 no.6 s.312
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• pp.1-8
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• 2006

Many researches on path planning and obstacle avoidance for the fundamentals of mobile robot have been done recently. Informations from various sensors can be used to find obstacles and plan feasible path. In spite of many solutions of finding optimal path, each can be applied in only a constrained condition. This means that it is difficult to find university good algorithm. An optimal path with a complicated computation generates a time delay which cannot avoid moving obstacles. In this paper, we propose an algorithm of path planning and obstacle avoidance for mobile robot. We call the proposed method Random Access Sequence(RAS) method. In the proposed method, a small region is set first and numbers are assigned to its neighbors, then the path is selected using these numbers and cumulative numbers. It has an advantage of fast planning time and completeness of path if one exists. This means that new path selection may be possible within short time and that helps a robot to avoid obstacle in dynamic environments. Using the information of the start and destination position, the RAS can be performed for collision-free navigation by reforming feasible paths repeatedly in dynamic environments.

• Proceedings of the Korea Air Pollution Research Association Conference
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• 2000.11a
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• pp.176-178
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• 2000

대기경계층내에서의 흐름은 평균류, 난류(Turbulence) 그리고 파동(wave) 3가지로 분류되는데 수평적으로 수 ms$^{-1}$ 연직적으로 수 cms$^{-1}$의 평균류에 의해서 수중기, 운동량, 열, 오염물질의 수송이 일어나며 이것들은 난류에 의해서 연직적 수송이 일어 난다. 그리고 평균류의 시어(shear)나 평균류가 장애물을 만나면서 형성되는 파동에 의해서 운동량, 에너지 등의 수송이 이루어진다(Stull., 1988). (중략)

• Journal of Korea Game Society
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• v.18 no.3
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• pp.113-122
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• 2018

In this paper, we will discuss planning and production of VR contents for effective racing drone steering training. In the real world, direct racing drone training training is obviously a space and economic limit. We propose through the production of VR-based drone infiltration action game as a solution to these limitations and try to improve effective drone handling ability. Especially, we designed the virtual reality contents in a similar environment by using the similarity of FPV goggles and HMD based VR, and designed virtual drones, maps and obstacles considering the characteristics of the structures used in racing drone and drone racing. Also, we tried to increase the user's immersion and presence by increasing difficulty level of obstacles.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.1
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• pp.153-159
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• 2012

Driver's view has blind spot of automobile surroundings due to physical components of automobile architecture. Obstacles on blind spot are the cause of car destruction and car accidents. Cars which produced in recent have obstacle detection sensors and rear view cameras which provide information of obstacles on the blind sopt, and have also AVM(Around View Monitoring) which provides automobile surroundings for driver's safe driving. During a low-speed travel while parking or moving in a narrow street, a driver get help for safe driving by taking information of automobile surroundings using the above-mentioned devices. In this paper, we present a design and implementation of a 4-sided monitoring (4SM) system, which helps a driver see an integrated view of a vehicle's perimeter at a glance, using a car PC connected to four cameras installed on the front, rear, left, and right sides.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.8
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• pp.1503-1517
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• 1994

Intelligent Motion Planning System(IMPS) is presented for a robot to achieve an efficient path toward the given target point in two dimensional unknown environment is constructed with unrestricted obstacle shapes. IMPS consists of three components for making intelligent motion. These components are real-time motion planning algorithm based on a discontinous boundary method, fuzzy neural network decision system for heuristic knowledge representation, and world modeling with forgetting and reinforcing memory cells. First of all, in real-time motion planning algorithm, the behavior-based architectural method is used to generate subgoal. A behavior generates a subgoal independently by using the method of discontinuous boundary in sensed area. The discontinuous boundary method is a new proposed fast obstacle avoidance algorithm. The second component is fuzzy neural network decision system for accomplishing the subgoal. The heuristic rules are imbedded on the fuzzy neural network to make an intelligent decision. The last one is a forgetting, reinforcing memory technique for the construction of external world map. The activation values of all activated memory cells in grid space are decreased monotonically and after all they are burned out. Therefore, after sufficient journey, robot can have a stationary world map even if the dynaic obstacles exist. Using the IMPS, several simulations show the efficient achievement of target point in unknown enviroment with obstcles of various shapes.