A relative mapping algorithm

This paper introduces a Relative Mapping Algorithm. This algorithm presents a new way of looking at the SLAM problem that does not use Probability, Iterative Closest Point, or Scan Matching techniques. A map of landmarks is generated by using the average relative location difference between landmarks. This means the algorithm does not use any known, estimated or predicted movement or position data. In addition, the Relative Mapping Algorithm has the capability to identify dynamic landmarks using a binning algorithm. The algorithm is shown to have a fast constant time O(nalogna) computation complexity where na is the average quantity of points that are visible. In limiting testing the accuracy of the Relative Mapping Algorithm is shown to be comparable to the Extended Kalman Filter.