A new state vector and a map joining algorithm for range-only SLAM

This paper presents a new state vector and a map joining algorithm for range-only SLAM problems. Local maps are built by least squares optimization using the new state vector and a landmark initialization strategy which is an improvement on our preliminary work [1]. The map joining algorithm combines the local maps using least squares optimization to maintain the estimation consistency. Both the local map building and the map joining algorithm maintain a list of “unused range observations” to minimize the potential for information loss. The accuracy of the proposed method is evaluated using a simulation dataset, and an experimental dataset provided by the Robotics Institute at Carnegie Mellon University (CMU).