• 전자공학회논문지 IE
• /
• v.43 no.1
• /
• pp.59-66
• /
• 2006

In this study, we have proposed a motion equation to control synchro drive mobile robot, a path plan to compute and track the best path to given destination and a technique utilizing uniform distribution and cluster management based Monte Carlo localization to have track current position of moving robot. In the localization test which was repeated 73 times resulted as following. The average process time of original Monte Carlo localization was 12.8ms. The proposed cluster management Monte Carlo localization resulted 9.3ms. Also the proposed method resulted correctly in the cases where original method failed.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.8 no.4
• /
• pp.27-35
• /
• 1998

Navigation is a method to direct a mobile robot without collision when traversing the environment. This is to reach a destination without getting lost. In this paper, global and local path planning in fixed obstacle and moving obstacle using genetic algorithm are presented. First, mobile robot searches optimal global path using genetic algorithm without falling into local minima. Then if it finds a unknown obstacle, it searches new path without crashing obstacle. Also if there is a moving obstacle, mobile robot searches new optimal path without colliding with the obstacles. Various simulation results show the proposed algorithm can search a shortest path effectively.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.13 no.1
• /
• pp.18-23
• /
• 2003

This paper presents new algorithms of path planning and obstacle avoidance for an autonomous mobile robot to navigate under unknown environments in the real time. Temporary targets are set up by distance variation method and then the algorithms of trajectory planning and obstacle avoidance are designed using fuzzy rules. It is shown by computer simulation that these algorithms are working well. Furthermore, an autonomous mobile robot was constructed to implement and test these algorithms in the real field. The experimental results are also satisfactory just like those of computer simulation.

• 제어로봇시스템학회:학술대회논문집
• /
• 1996.10b
• /
• pp.1189-1192
• /
• 1996

Navigation is a science of directing a mobile robot as traversing the environment. The purpose of navigation is to reach a destination without getting lost or crashing into any obstacles. In this paper, we use a genetic algorithm for navigation. Genetic algorithm searches for path in the entire, continuous free space and unifies global path planning and local path planning. It is the efficient and effective method when compared with navigators using traditional approaches.

• 제어로봇시스템학회:학술대회논문집
• /
• 1996.10b
• /
• pp.1193-1196
• /
• 1996

Genetic algorithm(GA) is useful to find optimal solution without any special mathematical modeling. This study presents to search optimal path of Autonomous Mobile Robot(AMR) by using GA without encoding and decoding procedure. Therefore, this paper shows that the proposed algorithm using GA can reduce the computation time to search the optimal path.

• Journal of Institute of Control, Robotics and Systems
• /
• v.5 no.7
• /
• pp.836-840
• /
• 1999

Linear motion and angular motion in task space are handled separately in joint velocity planning for redundant robot manipulators. In solving inverse kinematic equations with given joint velocity limits, we consider the order of priority for linear motion and angular motion. The proposed method will be useful in such applications where only linear motions are important than angular motions or vice versa.

• 제어로봇시스템학회:학술대회논문집
• /
• 2000.10a
• /
• pp.418-418
• /
• 2000

This paper proposes a path planning algorithm for mobile robot. To generate an optimal path and minimum time path for a mobile robot, we use the Genetic Algorithm(GA) and Visibility Graph. After finding a minimum-distance between start and goal point, the path is revised to find the minimum time path by path-smoothing algorithm. Simulation results show that the proposed algorithms are more effective.

• Proceedings of the KIEE Conference
• /
• 2002.07d
• /
• pp.2427-2429
• /
• 2002

본 논문에서는, 지붕위로 뛰어오르기 위하여 벽의 반동을 이용하는 고양이의 운동상태를 흉내내어 수직의 방향으로 운동하는 고양이 로봇 시스템을 연구한다. 또한 이러한 로봇 시스템의 3-link 부분시스템의 운동은 slider-link에서 구속되어지고, 또한 singular자세를 쉽게 피할 수 있는 운동계획방법(motion planning method)을 제안한다. 제안되어진 연구결과는 수직동작에 대한 메카니즘에 유용한 방법이고 이론적 개념, 모델링, 그리고 제어를 논의한다. 마지막으로, 모의실험을 통한 결과로서 제안되어진 방법의 유용성을 설명한다.

• Proceedings of the Korean Information Science Society Conference
• /
• 2006.10b
• /
• pp.254-259
• /
• 2006

전통적인 인공지능 계획방식은 완전한 월드 상태모델과 시스템 동작모델에 기초하여 처음부터 자동으로 작업계획을 생성하려는 접근방식이다. 그러나 지능로봇제어와 같이 불확실성과 가변성이 높은 실 세계 응용분야에서 이와 같은 전통적인 인공지능 계획방식은 효과를 얻기 어렵다. 반면에 많은 실 세계 응용분야에서는 그 분야에서 이미 잘 알려져 있는 작업 영역지식이나 제어지식들이 존재하며, 이들을 효과적으로 이용하는 것이 매우 중요하다. 이러한 방법 중의 하나로서 복잡도가 높은 작업계획을 전문가가 직접 편집해서 입력하는 방식이 널리 쓰인다. 기본 동작모델과는 달리, 일반적으로 작업계획 표현언어는 복잡한 제어구조를 포함하는 하나의 작업 프로세스로 계획을 표현한다. 따라서 이러한 복잡한 절차적 지식인 작업계획을 편집하고 검증하기 위해서는 편리한 모델링 도구의 개발이 필요하다. 본 연구에서는 PRS 계열의 작업계획을 비주얼 환경에서 편집할 수 있고, 가상 시뮬레이션 기능과 작업 계획기와의 연동 기능을 갖춘 PKM시스템의 설계와 구현에 대해 설명한다.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2008.06a
• /
• pp.473-474
• /
• 2008