Heterogeneous ant colony optimization algorithm for global path planning of mobile robot = 이동 로봇의 전역 경로 계획을 위한 이종의 개미 군집 최적화 알고리즘 개발

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Mobile robot applications are found in a wide range of areas and demand for applications rises nowadays, which increases the study of mobile robotics. A path planning problem is one of the important issues. The path planning problem is to find a collision-free and optimal path for a mobile robot from a start point to a goal point in the given environment. There are many algorithms for the path planning of a mobile robot. Ant Colony Optimization (ACO) algorithm is one of the these algorithms. The first ACO algorithm has been successfully applied in the combinatorial optimization problems such as Traveling Salesman Problem (TSP) and Quadratic Assignment Problem (QAP). The path planning problem for the mobile robot is also one of the combinatorial optimization problems and there are many studies of the ACO algorithms for the path planning. However, these algorithms followed the lead of the previous ACO algorithm that applied the first time. As a result of these follow, it takes a lot of time to get the solution and it is not to easy to obtain the optimal path every time. It is also difficult to apply to the more complex and big-size maps that need increases. The study of path planning can be divided in two classes: local and global. In the local planning case, the planning is based on the information given by sensors (ultrasonic, infrared, laser, cameras) installed on the robot. So this planning provides details about the local and unknown environment in real-time. On the other hand, in the global planning case, the model of environment is precisely defined and the planning is based on the information given previously. This approach improves the convergence towards the goal point. In the global path planning problem, we need to express the given environment as a considerable type of representation. There are generally four different types of representation. Among them, the composite-space map method is a very efficient and widely used. In the composite-space m...
Lee, Ju-Jangresearcher이주장researcher
한국과학기술원 : 로봇공학학제전공,
Issue Date
327249/325007  / 020073366

학위논문(석사) - 한국과학기술원 : 로봇공학학제전공, 2009. 8., [ viii, 45 p. ]


Ant Colony Optimization; Path Planning; Mobile Robot; Heterogeneous Ants; 개미 군집 최적화; 경로 계획; 이동 로봇; 이종의 개미

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