Perception and Navigation Modeling in Humans and Intelligent Systems

The purpose of this study is to present a model based on similarities in human navigation and robot navigation. It uses a hierarchical structure in three levels of landmarks, route, and survey knowledge. Recent cognitive models suggest that people use these types of spatial knowledge to perform many daily tasks. A similar approach was used for the robot navigation. The robot was able to finish the course successfully. This is an attempt to use biologically inspired theories in robotics and provide a test bed for biological hypotheses. INTRODUCTION Human and robot navigation have similarities and differences. The basic navigation issues are the same. Therefore, general theoretical and analytical approaches dealing with navigation in both areas can be integrated and both fields can benefit from each other. The difference is in how researches in each area deal with the problem. In human navigation the main question is how human processes information and what is the mechanism that enables humans and animals to navigate. On the other hand robotics researchers are looking for techniques to implement navigational abilities in real applications and whether or not it is biologically inspired is not an issue. Two approaches are complementary. Biological systems proof that an efficient and practical navigation system is achievable. On the other hand, robotics research can provide a valuable tool to test biological hypotheses. It can isolate a specific problem and examine psychological and biological questions. This paper is a part of studies aiming toward the human perception processing. The purpose of these studies is to develop a model for computing on the perceptions that lie in the natural language and to implement the model for the robot control that is influenced by human behavior. The goal is to enhance the mobile robot technology by adding this perception-processing model to current state of the art, which mainly is based on converting the propositions to measurements and not computing on perceptions directly. The proposed research tries to offer a complementary approach to the traditional methods and it is not a substitute for them. It tries to explore similarities and differences of navigation in humans and robots and present a model for the perception-based navigation.