• Journal of the Korea Institute of Military Science and Technology
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• v.23 no.4
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• pp.407-416
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• 2020

Recent complex battle field demands Network Centric Warfare(NCW) ability to control various parts into a cohesive unit. In path planning filed, the NCW ability increases complexity of path planning algorithm, and it has to consider a communication coverage map as well as traditional parameters such as minimum radar exposure and survivability. In this paper, pros and cons of various propagation models are summarized, and we suggest a coverage map generation method using a Longley-Rice propagation model. Previous coverage map based on line of sight has significant discontinuities that limits selection of path planning algorithms such as Dijkstra and fast marching only. If there is method to remove discontinuities in the coverage map, optimization based path planning algorithms such as trajectory optimization and Particle Swarm Optimization(PSO) can also be used. In this paper, the Longley-Rice propagation model is used to calculate continuous RF strengths, and convert the strength data using smoothed leaky BER for the coverage map. In addition, we also suggest other types of rough coverage map generation using a lookup table method with simple inputs such as terrain type and antenna heights only. The implemented communication coverage map can be used various path planning algorithms, especially in the optimization based algorithms.

• Proceedings of the KIEE Conference
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• 2005.05a
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• pp.252-254
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• 2005

Completer coverage path planning requires the robot path to cover every part of the workspace, which is an essential issue in cleaning robots and many other robotic applications such as vacuum robots and painter robots. In this paper, a novel Water Flowing Algorithm (WFA) is proposed for cleaning robots to complete coverage path planning in unknown environment without obstacles. The robot covers the whole workspace just like that water fills up a container. First the robot goes to the lowest point in the workspace just like water flows to the bottom of the container. At last the robot will come to highest point in the workspace just like water overflows from the container and simultaneously the robot has covered the whole workspace. The computer simulation results show that the proposed algorithm enable the robot to plan complete coverage paths.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.10
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• pp.1047-1055
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• 2009

Since nuclear and chemical materials could damage people and disturb battlefield missions in a wide region, nuclear/chemical reconnaissance systems utilizing multiple mobile robots are highly desirable for rapid and safe reconnaissance. In this paper, we design a nuclear/chemical reconnaissance system including mobile robots. Also we propose time-efficient trajectory planning algorithms using grid coverage and contour finding methods for reconnaissance operation. For grid coverage, we performed in analysis on time consumption for various trajectory patterns generated by straight lines and arcs. We proposed BCF (Bounded Contour Finding) and BCFEP (Bounded Contour Finding with Ellipse Prediction) algorithms for contour finding. With these grid coverage and contour finding algorithms, we suggest trajectory planning algorithms for single, two or four mobile robots. Various simulations reveal that the proposed algorithms improve time-efficiency in nuclear/chemical reconnaissance missions in the given area. Also we conduct basic experiments using a commercial mobile robot and verify the time efficiency of the proposed contour finding algorithms.

• The Journal of Korea Robotics Society
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• v.2 no.4
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• pp.304-309
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• 2007

This paper describes an efficient path generation method for area coverage. Its applications include robots for de-mining, cleaning, painting, and so on. Our method is basically based on a divide and conquer strategy. We developed a novel cell decomposition algorithm that divides a given area into several cells. Each cell is covered by a robot motion that requires minimum time to cover the cell. Using this method, completeness and time efficiency of coverage are easily achieved. For the completeness of coverage in dynamic environments, we also propose a path following method that makes the robot cover missed areas as a result of the presence of unknown obstacles. The effectiveness of the method is verified using computer simulations.

• International journal of advanced smart convergence
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• v.12 no.4
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• pp.8-19
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• 2023

This paper presents advancement in multi- unmanned aerial vehicle (UAV) cooperative area surveillance, focusing on optimizing UAV route planning through the application of genetic algorithms. Addressing the complexities of comprehensive coverage, two real-time dynamic path planning methods are introduced, leveraging genetic algorithms to enhance surveillance efficiency while accounting for flight constraints. These methodologies adapt multi-UAV routes by encoding turning angles and employing coverage-driven fitness functions, facilitating real-time monitoring optimization. The paper introduces a novel path planning model for scenarios where UAVs navigate collaboratively without predetermined destinations during regional surveillance. Empirical evaluations confirm the effectiveness of the proposed methods, showcasing improved coverage and heightened efficiency in multi-UAV path planning. Furthermore, we introduce innovative optimization strategies, (Foresightedness and Multi-step) offering distinct trade-offs between solution quality and computational time. This research contributes innovative solutions to the intricate challenges of cooperative area surveillance, showcasing the transformative potential of genetic algorithms in multi-UAV technology. By enabling smarter route planning, these methods underscore the feasibility of more efficient, adaptable, and intelligent cooperative surveillance missions.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.7
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• pp.211-217
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• 2019

In an complicated battlefield environment, information from enemy's camp is an important factor in carrying out military operations. For obtaining this information, the number of UAVs that can be deployed to the mission without our forces' loss and at low cost is increasing. Because the mission environment has anti-aircraft weapons, mission space is needed for UAV to guarantee survivability without being killed. The concept of Configuration Space is used to define the mission space considering with range of weapons and detect range of UAV. UAV must visit whole given area to obtain the information and perform Coverage Path Planning for this. Based on threats to UAV and importance of information that will be obtained, area that UAV should visit first is defined. Grid Map is generated and mapping threat information to each grid for UAV path planning. On this study, coverage conditions and path planning procedures are presented based on the threat information on Grid Map, and mission space is expanded to improve detection efficiency. Finally, simulations are performed, and results are presented using the suggested UAV path planning method in this study.

• The Journal of Korea Robotics Society
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• v.6 no.3
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• pp.255-262
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• 2011

Many intelligent robots have to be given environmental information to perform tasks. In this paper an intelligent robot, that is, a cleaning robot used a sensor fusing method of two sensors: LRF and StarGazer, and then was able to obtain the information. Throughout wall following using laser displacement sensor, LRF, the working area is built during the robot turn one cycle around the area. After the process of wall following, a path planning which is able to execute the work effectively is established using flow network algorithm. This paper describes an algorithm for minimal turning complete coverage path planning for intelligent robots. This algorithm divides the whole working area by cellular decomposition, and then provides the path planning among the cells employing flow networks. It also provides specific path planning inside each cell guaranteeing the minimal turning of the robots. The proposed algorithm is applied to two different working areas, and verified that it is an optimal path planning method.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.9
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• pp.789-794
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• 2005

This paper describes an algorithm for minimal turning complete coverage Path planning for cleaning robots. This algorithm divides the whole cleaning area by cellular decomposition, and then provides the path planning among the cells employing a flow network. It also provides specific path planning inside each cell guaranteeing the minimal turning of the robots. The minimal turning of the robots is directly related to the faster motion and energy saving. The proposed algorithm is compared with previous approaches in simulation and the result shows the validity of the algorithm.

• Proceedings of the Korea Information Processing Society Conference
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• 2002.11c
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• pp.2431-2434
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• 2002

본 논문에서는 전체 영역 경로 계획인 CCPP(Complete Coverage Path Planning)를 이용해 전 청소 영역을 청소하는 방법을 나타내고 청소영역을 해석 하였다. 그리고, Template방법에 CD(Cell Decomposition)을 접목시킨 방법을 이용해 청소영역을 청소 후 재 경로계획으로 청소 안된 영역을 효율적으로 청소하는 방법을 연구하였다. 또한 청소기의 회전 및 직선 모션에 따른 청소 영역을 비교 해석해 최적 시간과 거리에 따른 경로 계획을 살펴보았다.

• Proceedings of the Korea Information Processing Society Conference
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• 2003.11b
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• pp.639-642
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• 2003

본 논문에서는 청소로봇이 전 청소 영역을 CCPP(Complete Coverage Path Planning)를 이용해 경로를 생성한 후 재 경로계획 시 장애물의 미소한 변화로도 기존에 생성한 전 경로패턴을 바꾸지 않고 수정 할 수 있는 CD(Cell Decomposition)와 FN(Flow Network)을 이용한 CCPP 방식을 제안 하였다. 그리고 제안된 경로 계획에 대해 시뮬레이션으로 결과를 제시하였다.