Increasing Slam Performance By Integrating Grid And Topology Map

The technique of simultaneous localization and mapping is the most important research topic in mobile robotics. In the process of building a map in its available memory, the robot memorizes environmental information on the plane of grid or topology. Several approaches about this technique have been presented so far, but most of them use mapping technique as either grid-based map or topology-based map. In this paper we propose a frame of solving the SLAM problem of linking map covering, map building, localizing, path finding and obstacle avoiding in an automated way. Some algorithms integrating grid and topology map are considered and they make the SLAM performance faster and more stable. The proposed scheme uses an occupancy grid map in representing the environment and then formulates topological information in path finding by Dijikstra algorithm. The mapping process is shown and the shortest path is decided on grid based map. Then topological information such as direction, distance are calculated on a simulator program then transmitted to robot hardware devices. The localization process and the dynamic obstacle avoidance can be accomplished by topological information on the grid map. While mapping and moving, pose of the robot is adjusted for correct localization by implementing additional pixel based image layer and tracking features. A laser range finder and electronic compass systems are implemented on the mobile robot and DC geared motor wheels are individually controlled by PD based adaptive way. Simulations and experimental results show performance and efficiency of the proposed scheme.