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김동원(Dong-W. Kim),김주형(Joo-Hyung Kim),곽환주(Whan-Joo Kwak) 한국컴퓨터정보학회 2010 한국컴퓨터정보학회 학술발표논문집 Vol.18 No.2
본 논문에서는 포텐셜 필드 방법과 퍼지로직 시스템을 이용하여 멀티 모바일 로봇의 충돌회피를 위한 경로계획을 연구한다. 잘 알려진 포텐셜 필드 방법은 멀티 모바일 로봇 시스템에 있어서 각각의 로봇에 대한 전역경로를 계획하기 위해 사용되었으며, 퍼지로직 시스템은 각 로봇에 근접하는 혹은 진행하는 로봇의 경로를 가로막는 장애물과의 충돌을 피하고 안전하게 목적지에 도달하기 위한 지역경로를 계획하기 위해 이용되었다.
김동원(Dong W. Kim),김윤회(Yoon-Hoe Kim),박성욱(Sung-Wook Park),박종욱(Jong-Wook Park) 한국정보기술학회 2015 한국정보기술학회논문지 Vol.13 No.6
This paper proposes a method of designing the tele-monitoring system for marine diesel engine. The needs of tele-monitoring system of diesel engine occurs when engine customers and engine test engineers want to monitor operating status in real time from a marine diesel engine being tested at a test facility remotely located. This tele-monitoring system allows customers and test engineers to view their engine test sites from anywhere, anytime in the world. In this paper it is used that web-based monitoring server/client, network cameras and wireless networking technologies such as handheld devices and ZigBee technology. The result shows that the tele-monitoring methods get better for the safety, efficiency of engine test and convenient environment.
김동원(Dong W. Kim),김낙현(Nak-Hyun Kim),박귀태(Gwi-Tae Park) 제어로봇시스템학회 2010 제어·로봇·시스템학회 논문지 Vol.16 No.10
This paper handles ZMP based control that is inspired by neural networks for humanoid robot walking on varying sloped surfaces. Humanoid robots are currently one of the most exciting research topics in the field of robotics, and maintaining stability while they are standing, walking or moving is a key concern. To ensure a steady and smooth walking gait of such robots, a feedforward type of neural network architecture, trained by the back propagation algorithm is employed. The inputs and outputs of the neural network architecture are the ZMPx and ZMPy errors of the robot, and the x, y positions of the robot, respectively. The neural network developed allows the controller to generate the desired balance of the robot positions, resulting in a steady gait for the robot as it moves around on a flat floor, and when it is descending slope. In this paper, experiments of humanoid robot walking are carried out, in which the actual position data from a prototype robot are measured in real time situations, and fed into a neural network inspired controller designed for stable bipedal walking.
Multi-Mobile Robot System with Fuzzy Rule based Structure in Collision avoidance
Dong W. Kim(김동원),Chong-Ho Yi(이종호) 제어로봇시스템학회 2010 제어·로봇·시스템학회 논문지 Vol.16 No.3
This paper describes a multi-mobile robot system with fuzzy rule based structure in collision avoidance. Collision avoidance is an important function to perform a given task collaboratively and cooperatively in multi-mobile robot environments. So the important but challenging problem is handled in this paper. Considered obstacles for collision avoidance between multi mobile robots are static, dynamic, or both of them at the same time. Using the fuzzy rule based structure, distance and angle from a robot to obstacles are described as fuzzy linguistic values and steering angle for the robot are updated from the collision environments. As a result, the multi-mobile robot can modify a global path from a robot itself to its own target. In addition, avoiding collision with static or dynamic obstacles for the robot system can be achieved. Simulation based experimental results are given to show usefulness of this method.
자율 다개체 모바일 로봇 시스템의 동적 장애물 회피 구현
김동원(Dong W. Kim),이종호(Cho-Ho Yi) 한국컴퓨터정보학회 2013 韓國컴퓨터情報學會論文誌 Vol.18 No.1
자율적인 다개체 모바일 로봇 시스템에 관해 경로 계획과 충돌회피는 중요한 기능이며 동시에 협력과 협동적으로 주어진 일을 수행하는데 필요한 기능이다. 본 논문에서는 이러한 중요하고도 도전적인 문제를 다룬다. 제안된 방법은 포텐셜 필드 방법과 퍼지로직 시스템에 기반을 두고 있다. 첫째로, 전역경로 계획은 포텐셜 필드를 이용하여 로봇이 목적지까지 가는데 비용을 최소화할 수 있는 경로를 선택한다. 그러고 나서 지역경로 계획은 퍼지로직 시스템을 이용하여 정적이거나 동적인 장애물과의 충돌을 피하기 위해 전역경로에서 경로를 변경시킨다. 본 논문에서는 각각의 로봇은 독립적으로 목적지를 선택하며 동시에 다른 로봇은 동적인 장애물로 고려한다. 또한 장애물의 움직임을 예측할 필요도 없다. 이러한 과정은 각각의 로봇이 해당되는 목적지를 찾을 때 까지 지속된다. 이 방법을 테스트하기 위해 자율 다개체 로봇 시뮬레이터(AMMRS)를 개발했으며 시뮬레이션과 실험기반의 결과물을 제공한다. 본 결과는 다개체 모바일 로봇 시스템에 대하여 경로계획과 충돌회피 전략이 효율적이며 유용하다는 것을 보인다. 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.