Networked Robots Path Planning Using Simultaneous Localization and Mapping Algorithm

Multi-robot map merging is an essential task for cooperative robots navigation. Each robot is building its own local map with different reference. To merge these maps to global one, the transformation between the local maps must be computed so that we have one reference. Data association and inter robot observations are two alignment methods which are used to compute the transformation parameters. Data association uses correspondences between each pair of maps and inter robot observations uses robot-robot observations when robots observed each other. This paper evaluates these two alignment methods; and presents an improved method for map alignment. Robots will be able to choose the suitable one of them depending on the degree of overlap between partial maps to merge these maps accurately. Navigation path for a single robot is used for testing the implemented map.