Abstract-This paper presents results of our work in development of a genetic algorithm based path-planning algorithm for local obstacle avoidance (local feasible path) of a mobile robot in a given search space. The method tries to find not only a valid path but also an optimal one. The objectives are to minimize the length of the path and the number of turns. The proposed pathplanning method allows a free movement of the robot in any direction so that the path-planner can handle complicated search spaces.

No abstract

No abstract

Abstract-System security continues to be of increasing importance. To effectively address both natural and intentional threats to large systems, the threats must be cataloged and analyzed. Extremely large and complex systems can have an accordingly large number of threat scenarios. Simply listing the threats and devising countermeasures for each is ineffective and not efficient. We describe a threat cataloging methodology whereby a large number of threats can be efficiently cataloged and analyzed for common features. This allows countermeasures to be formulated that address a large number of threats that share common features. The methodology utilizes MultipleValued Logic for describing the state of a large system and a multiple-valued decision diagram (MDD) for the threat catalog and analysis.Large System Security, Threat cataloging, MDD