• 한국산업융합학회 논문집
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• 제14권2호
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• pp.53-57
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• 2011

Military and commercial unmanned vehicle navigation systems are being actively studied in the field of robotics. In this study, GPS-based path generation algorithm Film Festival and the system can compensate for the shortcomings of applying a map-based path plan, the unmanned vehicle navigation systems to improve the performance of path planning algorithms are introduced.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 심포지엄 논문집 정보 및 제어부문
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• pp.249-251
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• 2005

In this paper, an algorithm of path planning and obstacle avoidance for mobile robot is proposed. 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. By processing assigned numbers all regions are covered and then the path from start to destination is selected by these numbers. The RAS has an advantage of fast planning because of simple operations. This implies that new path selection may be possible within a short time and helps a robot to avoid obstacles in any direction. The algorithm can be applied to unknown environments. When moving obstacles appear, a mobile robot avoids obstacles reactively. then new path is selected by RAS.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.120.3-120
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• 2001

We propose a new method of path planning for cleaning robots. Path planning problem for cleaning robots is different from conventional path planning problems in which finding a collision-free trajectory from a start point to a goal point is focused. In the case of cleaning robots, however, a planned path should cover all area to be cleaned. To resolve this problem in a systematic way, we propose a method based on a graph model as follows: at first, partition a given map into proper regions, then transform a divided region to a vertex and a connectivity between regions to an edge of a graph. Finally, a region is divided into sub-regions so that the graph has a unary tree which is the simplest Hamilton path. The effectiveness of the proposed method is shown by computer simulation results.

• 제어로봇시스템학회논문지
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• 제22권3호
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• pp.217-225
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• 2016

In this paper, we propose an improved path planning method and obstacle avoidance algorithm for two-wheel mobile robots, which can be effectively applied in an environment where obstacles can be represented by circles. Firstly, we briefly introduce the rapidly exploring random tree (RRT) and single polar polynomial (SPP) algorithm. Secondly, we present additional two methods for applying our proposed method. Thirdly, we propose a global path planning, smoothing and obstacle avoidance method that combines the RRT and SPP algorithms. Finally, we present a simulation using our proposed method and check the feasibility. This shows that proposed method is better than existing methods in terms of the optimality of the trajectory and the satisfaction of the kinematic constraints.

• 한국조명전기설비학회지:조명전기설비
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• 제13권2호
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• pp.164-164
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• 1999

An autonomous mobile vehicle for transport system must plan optimal path in work environment without human supervision and obstacle collision. This is to reach a destination without getting lost. In this paper, a genetic algorithm for global and local path planning and collision avoidance is proposed. The genetic algorithm searches for a path in the entire and continuous free space and unifies global path planning and local path planning. The simulation shows the proposed method is an efficient and effective method when compared with the traditional collision avoidance algorithms.

• 조명전기설비학회논문지
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• 제24권10호
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• pp.163-173
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• 2010

In multi-mobile robot environment, path planning and collision avoidance are important issue to perform a given task collaboratively and cooperatively. The proposed approach is based on a potential field method and fuzzy logic system. For a global path planner, potential field method is employed to select proper path of a corresponding robot and fuzzy logic system is utilized to avoid collisions with static or dynamic obstacles around the robot. This process is continued until the corresponding target of each robot is reached. To test this method, several simulation-based experimental results are given. The results show that the path planning and collision avoidance strategies are effective and useful for multi-mobile robot systems.

• 한국정밀공학회지
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• 제12권1호
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• pp.58-67
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• 1995

A path planning algorithm using a laser range finder are presented for real-tiem navigation of an autonomous guided vehicle. Considering that the laser range finder has the excellent resolution with respect to angular and distance measurements, a sophisticated local path planning algorithm is achieved by using the human's heuristic method. In the case of which the man knows not rhe path, but the goal direction, the man forwards to the goal direction, avoids obstacle if it appears, and selects the best pathway when there are multi-passable ways between objects. These heuristic principles are applied to the path decision of autonomous guided vehicle such as forward open, side open and no way. Also, the effectiveness of the established path planning algorithm is estimated by computer simulation in complex environment.

• 한국지능시스템학회:학술대회논문집
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• 한국지능시스템학회 2007년도 추계학술대회 학술발표 논문집
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• pp.176-179
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• 2007

In this paper, we develop the path planning algorithm using the improved Dijkstra algorithm and the particle swarm optimization. To get the optimal path, at first we construct the MAKLINK on the world environment and then make a graph associated with the MAKLINK. From the graph, we obtain the Dijkstra path between the starting point and the destination point. From the optimal path, we search the improved Dijkstra path using the graph. Finally, applying the particle swarm optimization to the improved Dijkstra path, we obtain the optimal path for the mobile robot. It turns out that the proposed method has better performance than the result in [1].

• 한국항행학회논문지
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• 제13권5호
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• pp.646-655
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• 2009

본 논문은 로봇 충돌회피 경로계획의 문제점을 해결하기 위해 진화된 모델에 근거한 새로운 경로탐색 전략을 소개한다. 최적화된 지능형 검색 방법으로 잘 알려진 유전자 알고리즘을 이용하여 로봇 경로계획 방법을 설계하였다. 염색체 안에 있는 유전자 인자로 경로점을 고찰해보면 주어진 맵에 대한 가능한 해법이제공된다. 생성된 염색체 간의 거리가 먼 경우 유사한 염색체에 대한 적합도로 간주할 수 있다. 경로계획에 있어 본 논문에서 제안한 유전자 알고리즘의 유효성을 증명하기위해 다양한 방법으로 시뮬레이션을 실시하였으며, 제안한 경로 검색 방법은 정지된 장애물이나 복잡한 장애물에도 사용될 수 있음을 증명하였다.

• 산업경영시스템학회지
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• 제35권1호
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• pp.39-46
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• 2012

An unmanned aerial vehicle (UAV) is a powered aerial vehicle that does not carry a human operator, uses aerodynamic forces to provide vehicle lift, can fly autonomously or be piloted remotely, can be expendable or recoverable, and can carry a lethal or non-lethal payload. An UAV is very important weapon system and is currently being employed in many military missions (surveillance, reconnaissance, communication relay, targeting, strike, etc.) in the war. To accomplish UAV's missions, guarantee of survivability should be preceded. The main objective of this study is a local path planning to maximize survivability for UAV on the battlefield of dynamic threats (obstacles, surface-to-air missiles, radar etc.). A local path planning is capable of producing a new path in response to environmental changes. This study suggests a $Smart$ $A^*$ (Smart A-star) algorithm for local path planning. The local path planned by $Smart$ $A^*$ algorithm is compared with the results of existing algorithms ($A^*$ $Replanner$, $D^*$) and evaluated performance of $Smart$ $A^*$ algorithm. The result of suggested algorithm gives the better solutions when compared with existing algorithms.