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

Publication Type:
Conference Proceeding
Citation:
2012 12th International Conference on Control, Automation, Robotics and Vision, ICARCV 2012, 2012, pp. 1024 - 1029
Issue Date:
2012-12-01
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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). © 2012 IEEE.
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