This paper presents a SLAM algorithm for a team of mobile robots exploring an indoor environment, described by adopting the M-Space representation of linear features. Each robot solves the SLAM problem independently. When the robots meet, the local maps are fused together using robot-to-robot relative range and bearing measurements. A map fusion technique, tailored to the specific feature representation adopted, is proposed. Moreover, the uncertainty affecting the resulting merged map is explicitly derived from the single-robot SLAM maps and the robot-to-robot measurement accuracy. Simulation experiments are presented showing a team composed of two robots performing SLAM in a real-world scenario. ©2010 IEEE.
Benedettelli, D., Garulli, A., Giannitrapani, A. (2010). Multi-robot SLAM using M-space feature representation. In Proceedings of the 49th IEEE Conference on Decision and Control (pp.3826-3831). New York : IEEE [10.1109/CDC.2010.5716942].
Multi-robot SLAM using M-space feature representation
Benedettelli D.;Garulli A.;Giannitrapani A.
2010-01-01
Abstract
This paper presents a SLAM algorithm for a team of mobile robots exploring an indoor environment, described by adopting the M-Space representation of linear features. Each robot solves the SLAM problem independently. When the robots meet, the local maps are fused together using robot-to-robot relative range and bearing measurements. A map fusion technique, tailored to the specific feature representation adopted, is proposed. Moreover, the uncertainty affecting the resulting merged map is explicitly derived from the single-robot SLAM maps and the robot-to-robot measurement accuracy. Simulation experiments are presented showing a team composed of two robots performing SLAM in a real-world scenario. ©2010 IEEE.
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https://hdl.handle.net/11365/19452
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