<title>Maintaining knowledge for an adaptive path-planning system</title>

Abstract

In this paper, we present a new approach to solve the mobile robot path planning problem with the consideration of the adaptability to task environmental changes due to unexpected obstacles. In order to accommodate these changes, newly discovered obstacles must be represented and included to update obstacle information. We propose a problem representation method to model the path planning problem. In this method, spatial knowledge described in terms of visibility, interference, and target obstacle is used to model the solution process. The knowledge inference process is based on traversability vectors, a mechanism to analyze spatial relation between geometric objects. We assume that an obstacle can be represented by a set of half-planes. Coefficients of the half-planes are stored as the basic world description. Changes on the obstacles can be accommodated by updating the stored coefficients. Thus, the planning system can always utilize the most recently updated obstacle information to plan for the path. This planning procedure is capable of generating the shortest path efficiently. We use a simulation example to show the capability of the proposed work.