A Knowledge-Based Robot Searching for an Unpredictable Goal under Unknown Environment

This paper describes a knowledge-based robot that explores an unknown environment for an unpredictable goal. Distinguishing characteristics of such environments for robotic navigation are that the goal’s position is unpredictable and some obstacles cannot be sensed directly. Considering such features we propose a search algorithm for finding the goal and a simplified DPLL to allow robotic reasoning. Moreover we demonstrate the completeness and the execution cost of the search algorithm and also support the completeness and soundness of the simplified DPLL. The set memory rules allow for computer processing limitations. In addition, the simulation results of randomly produced environments demonstrate the completeness, soundness and effectiveness of method.