Ant-Q agent System Based Path Optimization Service for a Multi- Objective Mobile Robot and Real World

A multi-objective mobile robot path planning algorithm based on improved Ant-Q agent system algorithm is proposed. The most Driver has Navigation system. It is convenient if him use the Navigation system. But, Navigation systems are not able to determine optimized driving routes considering that each driver has specific driving habits and propensities and many circumstantial changes are present in every trip. Therefore, We Propose a route recommendation system as part of the personalizing information method for navigation systems by the prey pursuit problem has been put to use in multi-agent research in addition to the food chain system using multiagents in a virtual grid space. In this paper, We suggest a limitless space like reality and a new algorithm to better explain reality using the existing grid space and obstacle environment. We suggest New algorithm is based Ant-Q(Ant Colony System – Q learning) algorithm. Ant-Q algorithms were inspired by work on the ant system (AS), a distributed algorithm for combinatorial optimization based on the metaphor of ant colonies which was recentl proposed in (Dorigo, 1992; Dorigo, Maniezzo and Colorni, 1996).