Universal autonomous robot navigation using quasi optimal path generation

Autonomous robot navigation is an important research field because these robots can solve problems where the human presence is impossible, dangerous, expensive, or uncomfortable. In this paper, a new hybrid autonomous navigation method is introduced. The algorithm is composed of visibility graph based global navigation and simple potential field based local navigation parts. It applies a new automated graph generation method which may become necessary if, because of the observed new obstacles, a new path should be generated. The quasi optimal route is found by applying the well known A* algorithm on the graph. The presented technique offers a quasi optimal universal navigation technique which can successfully be used in all, known, unknown, and dynamically changing environments.