Abstract
In many outdoor robotic applications several factors have to be taken into account during a path planning process. In different situations the importance of these factors vary. This paper presents a path planning method for mobile robots that incorporates decision theory to guide the search. A neural structure is proposed to determine the relative importance of the objectives that makes the robot capable of planning in unfamiliar situations. The method is able to handle an arbitrary number of objectives simultaneously and also enables the incorporation of human logic into the planning process. All parts of the algorithm suit real-time implementation.
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