• 전자공학회논문지 IE
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• 제48권3호
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• pp.26-32
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• 2011

본 논문은 화재라는 특수한 상황에서 대피자를 로봇에 비유하여 퍼텐셜 필드 방식으로 최적의 대피 경로를 탐색하는 방식을 제안한다. 장애물은 화재가 발생된 위치를 나타내게 되며, 한정된 공간에서 센서를 통해 화재가 발생한 위치를 확인할 수 있어서 전역적인 탐색이 가능해진다. 건물 내에 설치된 화재 감지 센서와 복합 감지 센서로부터 상황 정보를 습득하여 무선으로 서버에 전송하면 퍼텐셜 필드 방식으로 최적의 대피 경로를 탐색하여 유도등을 대피 방향으로 동작시키며 스마트 폰과 같은 모바일 단말에 무선을 이용하여 대피 경로 정보를 표시할 수 있게 된다. 시뮬레이션 환경에서 제안한 화재 대피 알고리즘의 기능 및 성능 테스트를 통해 제안 알고리즘의 성능을 확인할 수 있었다.

• 한국항행학회논문지
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• 제16권1호
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• pp.122-130
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• 2012

항공기 분리보증은 자유비행의 핵심요구사항이다. 본 논문에서는 위임권한 확대, 공역 효율성 문제 등 자유비행의 실증적 문제해결을 위해 자율형 운항 알고리즘을 제안하고, 제안된 알고리즘과 포텐셜 필드 알고리즘을 모델링하여 두 가지 조건의 시나리오 상황에서 항공기 성능 데이터를 활용, 알고리즘 성능 및 충돌해결과 운항 자율성 효과 등을 측정하였다. 실험결과 자유비행 공역 하에서 자율형 운항 알고리즘이 포텐셜 필드 알고리즘보다 알고리즘 성능, 충돌해결, 운항 자율성 효과 측면에서 우수하였다.

• 한국생산제조학회지
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• 제7권1호
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• pp.9-21
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• 1998

This paper a new solution approach to moving obstacle avoidance problem of a mobile robot. A new concept avoidability measure (AVM) is defined to describe the state of a pair of a robot and an obstacle regarding the collision between them. As an AVM, virtual distance function (VDF), is derived as a function of the distance from the obstacle to the robot and outward speed of the obstacle relative to the robot. By keeping the virtual distance above some positive limit value, the robot avoids the obstacle. In terms of the VDF ,an artificial potential field is constructed to repel the robot away from the obstacle and to attract the robot toward a goal location. At every sampling time, the artificial potential field is updated and the force driving the robot is derived from the gradient of the artificial potential field. The suggested algorithm drives the robot to avoid moving obstacles in real time. Since the algorithm considers the mobility of the obstacle as well as the distance, it is effective for moving obstacle avoidance. Some simulation studies show the effectiveness of the proposed approach.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 1998년도 춘계학술대회 논문집
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• pp.88-93
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• 1998

This paper presents a new solution approach to moving obstacle avoidance problem for a mobile robot. A new concept avoidability measure(AVM) is defined to describe the state of a pair of a robot and an obstacle regarding the collision between them. As an AVM, virtual distance function(VDF) is derived as a function of the distance from the obstacle to the robot and outward speed of the obstacle relative to the robot. By keeping the virtual distance above some positive limit value, the robot avoids the obstacle. In terns of the VDF, an artificial potential field is constructed to repel the robot away from the obstacle and to attract the robot toward a goal location. At every sampling time, the artificial potential field is updated and the force driving the robot is derived form the gradient of the artificial potential field. The suggested algorithm drives the robot to avoid moving obstacles in real time. Since the algorithm considers the mobility of the obstacle as well as the distance, it is effective for moving obstacle avoidance. Some simulation studies show the effectiveness of the proposed approach.

• 한국지능시스템학회논문지
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• 제19권5호
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• pp.737-742
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• 2009

청소 로봇, 관광 안내 로봇부터 우주 탐사로봇까지 자율이동로봇의 응용분야가 넓어짐에 따라서 자율이동로봇의 인기는 급속도로 높아지고 있다. 하지만 동적인 환경 내에서 자율이동로봇의 안전한 네비게이션을 위한 만족스러운 제어 알고리즘은 여전히 연구 과제이다. 본 논문에서는 새로운 Potential field method를 이용한 제어 방법을 제안하였고, 컴퓨터 시뮬레이션을 통해 제안한 알고리즘을 실행하고 분석하였고, 이 실험 결과들로서 Potential field method를 사용한 행동(behavior)에 기반한 제어 시스템의 유효성을 나타내었다.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2001년도 The Pacific Aisan Confrence On Intelligent Systems 2001
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• pp.37-44
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• 2001

This paper describes the modeling of work environment for the extraction of abstract operation rules for cooperative work with multiple agent. We propose the modeling method using a potential field. In the method, it is applied to a box pushing problem, which is to move a box from a start to a goal b multiple agent. The agents follow the potential value when they move and work in the work environment. The work environment is represented as the grid space. The potential field is generated by Genetic Algorithm(GA) for each agent. GA explores the positions of a potential peak value in the grid space, and then the potential value stretching in the grid space is spread by a potential diffusion function in each grid. However it is difficult to explore suitable setting using hand coding of the position of peak potential value. Thus, we use an evlolutionary computation way because it is possible to explore the large search space. So we make experiments the environment modeling using the proposed method and verify the performance of the exploration by GA. And we classify some types from acquired the environment model and extract the abstract operation rule, As results, we find out some types of the environment models and operation rules by the observation, and the performance of GA exploration is almost same as the hand coding set because these are nearly same performance on the evaluation of the consumption of agent's energy and the work step from point to the goal point.

• 한국자동차공학회논문집
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• 제19권4호
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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.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제9권4호
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• pp.315-320
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• 2009

The popularity of autonomous mobile robots have been rapidly increasing due to their new emerging application areas, from room cleaning, tourist guidance to space explorations. However, the development of a satisfactory control algorithm that will enable the autonomous mobile robots to navigate safely especially in dynamic environments is still an open research problem. In this paper, a newly proposed potential field based control method is implemented, analyzed, and improvements are suggested based on experimental results obtained from simulations. The experimental results are presented to show the effectiveness of the behavior-based control using the proposed potential field generation technique.

• 제어로봇시스템학회논문지
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• 제3권2호
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• pp.169-178
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• 1997

This paper presents a new solution approach to moving obstacle avoidance problem of a robot. A new concept, avoidability measure(AVM) is defined to describe the state of a pair of a robot and an obstacle regarding the collision between them. As an AVM, virtual distance function(VDF) is derived as a function of three state variables: the distance from the obstacle to the robot, outward speed of the obstacle relative to the robot, and outward speed of the robot relative to the obstacle. By keeping the virtual distance above some positive limit value, the robot avoids the obstacle. In terms of the VDF, an artificial potential is constructed to repel the robot away from the obstacle and to attract the robot toward a goal location. At every sampling time, the artificial potential field is updated and the force driving the robot is derived from the gradient of the artificial potential field. The suggested algorithm drives the robot to avoid a moving obstacle in real time. Since the algorithm considers the mobility of the obstacle and robot as well as the distance, it is effective for moving obstacle avoidance. Some simulation studies show the effectiveness of the proposed approach.

• 로봇학회논문지
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• 제8권1호
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• pp.43-50
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• 2013

$A^*$ algorithm is a global path generation algorithm, and typically create a path using only the distance information. Therefore along the path, a moving vehicle is usually not be considered by driving characteristics. Deceleration at the corner is one of the driving characteristics of the vehicle. In this paper, considering this characteristic, a new evaluation function based path algorithm is proposed to decrease the number of driving path corner, in order to reduce the driving cost, such as driving time, fuel consumption and so on. Also the potential field method is applied for driving of UGV, which is robust against static and dynamic obstacle environment during following the generated path of the mobile robot under. The driving time and path following test was occurred by experiments based on a pseudo UGV, mobile robot in downscaled UGV's maximum and driving speed in corner. The experiment results were confirmed that the driving time by the proposed algorithm was decreased comparing with the results from $A^*$ algorithm.