• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.2
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• pp.187-191
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• 2012

This paper deals with a safe climbing path planning for unmanned automatic vehicles. Unlike the existing path planning schemes, the safety is the highest priority for our approach. To achieve this, the global potential field which includes a dangerous zone as well a given terrain information is generated, and the way-points are determined by using image processing such as the erosion operation. The proposed method can reduce the computation effort and the amount of information, and provide the safe climbing path which is similar to human's intuition.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.6
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• pp.687-693
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• 2012

In this paper, we propose a optimal deployment method for cooperative exploration of swarm robots. The proposed method consists of two parts such as optimal deployment and path planning. The optimal area deployment is proposed by the K-mean Algorithm and Voronoi tessellation. The path planning is proposed by the potential field method and A* Algorithm. Finally, the numerical experiments demonstrate the effectiveness and feasibility of the proposed method.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.1
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• pp.77-84
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• 2023

In autonomous robots, obstacle avoidance is a key feature. Potential Field is the most widely used method in this field. Such method requires real-time calculation of the nearest point of the obstacle from the robot, which involves difficulty of reliably segmenting the obstacle region from the distance sensor data profile. In this paper, Active Min-Depth Filter is introduced to obtain the nearest point of each obstacle using real-time calculation but without segmentation. Through simulations on various sensor noise environments, the robustness of the Active Min-Depth Filter could be confirmed, and successful results were obtained by applying real-world moving robots.

• 전자공학회논문지 IE
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• v.47 no.2
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• pp.66-72
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• 2010

In an autonomous multi-mobile robot environment, optimal path planning without collision which connects the beginning and ending point is essential and primary important. Many mobile robots should move autonomously without prior or given information about obstacles which are stationary or dynamic. Collision free optimal path planning for multi mobile robots is proposed in this paper. The proposed approach is based on a potential field method and fuzzy logic system. First, a global path planner using potential field method selects the shortest path from each robot to its own target. Then, a local path planner modifies the path and orientation from the global planner to avoid collisions with static and dynamic obstacles using a fuzzy logic system. To verify performance of this method, several simulation-based experimental are done and their results are discussed. These results show that the path planning and collision avoidance strategies are effective and useful for multi-mobile robot systems.

• Economic and Environmental Geology
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• v.33 no.3
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• pp.217-228
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• 2000

We use spectral correlation method to analyze gravity and magnetic anomalies of Euiseong Sub-basin for distribution of rock facies and gelogic structures. The analysis reveals distinct polarity between gravity and magnetic anomaly correlation ; intermediate to mafic intrusives, extrusives, and the Tertiary basin shows positive gravity (+G) and positive magnetic (+M) correlation. Granitic gneiss and felsic volcanics negative gravity 9-G) and negative magnetic (-M) correlation. The Palgongsan granite, felsic to mafic extrusives and Mesozoic granites are characterized by -G and + M correlation. +G and -M correlations in the sedimentary formations are interpreted by uplift of pre-Cretaceous basement rocks . The + G and + M correlation characteristics in northeastern part of Euiseong Sub-basin including the Tertiary sedimentary basin result from the uplift of crustal materials. Major axes of spectrally correlated amomalies have mostly NW-SE or NE-SW directions. The former is due to the intrusives along strike-slip faults, and the latter which is observed in sedimentary formations is related to geological structures of basement associated new insight into the boundary between Euiseong and Milyang Sub-basin.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1892-1893
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• 2011

본 논문에서는 Centroidal Voronoi Tessellation을 이용하여 군집로봇의 협조탐색을 위한 공간분할기법을 제안한다. 탐색공간은 Centroidal Voronoi Tessellation을 이용하여 분할한다. 전역 경로 계획 및 군집 로봇 간의 충돌 회피는 포텐셜 필드를 이용한다. 탐색공간에 밀도 함수를 사용하여 공간분할의 유동성을 부여한다. 마지막으로, 군집로봇의 협조탐색의 가능성을 시뮬레이션을 통하여 확인한다.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1890-1891
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• 2011

본 논문은 변형 가능한 타원형의 포메이션을 유지하기 위한 군집 로봇의 행동 동기화 알고리즘을 제안한다. 알고리즘은 매개 변수 함수를 이용한 타원형 포메이션에서의 포텐셜 필드 생성 부분과 개별 로봇이 타원으로 이동하기 위한 인력 및 충돌 회피를 위한 척력 함수 부분으로 나누어진다. 제안한 알고리즘은 시뮬레이션을 통해 군집 로봇의 행동을 제어하는데 효과적임을 입증하였다.

• Transactions of the Korean Society of Automotive Engineers
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• v.19 no.4
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• pp.8-15
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• 2011

This paper proposes a real-time navigation algorithm which integrates the artificial potential field (APF) for an unmanned vehicle in the unknown environment. This approach uses repulsive potential function around the obstacles to force the vehicle away and an attractive potential function around the goal to attract the vehicle. In this research, laser range finder is used as range sensor. An obstacle detected by the sensor creates repulsive vector. Differential global positioning system (DGPS) and digital compass are used to measure the current vehicle position and orientation. The measured vehicle position is also used to create attractive vector. This paper proposes a new concept of potential field based navigation which controls unmanned vehicle's speed and steering. The magnitude of repulsive force based on the proposed algorithm is designed not to be over the magnitude of attractive force while the magnitude is increased linearly as being closer to obstacle. Consequently, the vehicle experiences a generalized force toward the negative gradient of the total potential. This force drives the vehicle downhill towards its goal configuration until the vehicle reaches minimum potential and it stops. The effectiveness of the proposed APF for unmanned vehicle is verified through simulation and experiment.

• Journal of the Korea Society of Computer and Information
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• v.18 no.1
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• pp.11-19
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• 2013

For an autonomous multi-mobile robot system, path planning and collision avoidance are important functions used to perform a given task collaboratively and cooperatively. This study considers these important and challenging problems. The proposed approach is based on a potential field method and fuzzy logic system. First, a global path planner selects the paths of the robots that minimize the cost function from each robot to its own target using a potential field. Then, a local path planner modifies the path and orientation from the global planner to avoid collisions with static and dynamic obstacles using a fuzzy logic system. In this paper, each robot independently selects its destination and considers other robots as dynamic obstacles, and there is no need to predict the motion of obstacles. This process continues until the corresponding target of each robot is found. To test this method, an autonomous multi-mobile robot simulator (AMMRS) is developed, and both simulation-based and experimental results are given. The results show that the path planning and collision avoidance strategies are effective and useful for multi-mobile robot systems.

• Journal of the Society of Naval Architects of Korea
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• v.61 no.3
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• pp.170-184
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• 2024

With the advancement of autonomous navigation technology in maritime domain, there is an active research on swarming Unmanned Surface Vehicles (USVs) that can fulfill missions with low cost and high efficiency. In this study, we propose a formation control algorithm that maintains a certain shape when multiple unmanned surface vehicles operate in a swarm. In the case of swarming, individual USVs need to be able to accurately follow the target state and avoid collisions with obstacles or other vessels in the swarm. In order to generate guidance commands for swarm formation control, the potential field method has been a major focus of swarm control research, but the method using the potential field only uses the position information of obstacles or other ships, so it cannot effectively respond to moving targets and obstacles. In situations such as the formation change of a swarm of ships, the formation control is performed in a dense environment, so the position and velocity information of the target and nearby obstacles must be considered to effectively change the formation. In order to overcome these limitations, this paper applies a method that considers relative velocity to the potential field-based guidance law to improve target following and collision avoidance performance. Considering the relative velocity of the moving target, the potential field for nearby obstacles is newly defined by utilizing the concept of Velocity Obstacle (VO), and the effectiveness and efficiency of the proposed method is verified through swarm control simulation, and swarm control experiments using a small scaled unmanned surface vehicle platform.