title: A fast map merging algorithm in the field of multirobot SLAM.
abstract: In recent years, the research on single-robot simultaneous localization and mapping (SLAM) has made a great success. However, multirobot SLAM faces many challenging problems, including unknown robot poses, unshared map, and unstable communication. In this paper, a map merging algorithm based on virtual robot motion is proposed for multi-robot SLAM. The thinning algorithm is used to construct the skeleton of the grid map's empty area, and a mobile robot is simulated in one map. The simulated data is used as information sources in the other map to do partial map Monte Carlo localization; if localization succeeds, the relative pose hypotheses between the two maps can be computed easily. We verify these hypotheses using the rendezvous technique and use them as initial values to optimize the estimation by a heuristic random search algorithm.
authors.affiliation: School of Information Science and Engineering, Central South University, Changsha 410075, China ; School of Information Engineering, East China Jiaotong University, Nanchang 330013, China.
authors.forename: Yanli
authors.initials: Y
authors.lastname: Liu
authors.forename: Xiaoping
authors.initials: X
authors.lastname: Fan
authors.forename: Heng
authors.initials: H
authors.lastname: Zhang
mesh_terms: D000465:Algorithms; D003142:Communication; D003199:Computer Systems; D009010:Monte Carlo Method; D009038:Motion; D015203:Reproducibility of Results; D012371:Robotics / Q000295:instrumentation* / Q000379:methods*; D012984:Software