The mobile robot path planning involves finding the shortest and least difficult path from a start to a goal position in a given environment without collisions with known obstacles.
The main idea of case-based reasoning (CBR) is a presumption that similar tasks probably also have similar solutions. New tasks are solved by adapting old proved solutions of similar tasks to new conditions. Tasks and their solutions (cases) are stored in a case base.
The focal point of this paper is the proposition of a path planning method based on CBR combined with graph algorithms in the environment represented by a rectangular grid. On the basis of the experimental results obtained, it is possible to say that case-based reasoning can significantly save computation costs, particularly in large environments. and Obsahuje seznam literatury