Abstract
To effectively act on the same physical space, robots must first communicate to share and fuse the map of the area in which they operate. For long-term online operation, the merging of maps from heterogeneous devices must be fast and allow for scalable growth in both the number of clients and the size of the map. This paper presents a system which allows multiple clients to share and merge maps built from a state-of-the-art relative SLAM system. Maps can also be augmented with virtual elements that are consistently shared by all the clients. The visual-inertial mapping framework which underlies this system is discussed, along with the server architecture and novel integrated multi-session loop closure system. We show quantitative results of the system. The map fusion benefits are demonstrated with an example augmented reality application.
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This work is made possible with generous support from Google Project Tango.
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Morrison, J.G., Gálvez-López, D., Sibley, G. (2016). MOARSLAM: Multiple Operator Augmented RSLAM. In: Chong, NY., Cho, YJ. (eds) Distributed Autonomous Robotic Systems. Springer Tracts in Advanced Robotics, vol 112 . Springer, Tokyo. https://doi.org/10.1007/978-4-431-55879-8_9
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DOI: https://doi.org/10.1007/978-4-431-55879-8_9
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