Abstract
Autonomous robots need to perceive and represent their environments and act accordingly. Using simultaneous localization and mapping (SLAM) methods, robots can build maps of the environment which are efficient for localization and path planning as long as the environment remains unchanged. However, facility logistics environments are not static because pallets and other obstacles are stored temporarily.
This paper proposes a novel solution for updating maps of changing environments (i.e. environments with low-dynamic or semi-static objects) in real-time with multiple robots. Each robot is equipped with a laser range sensor and runs localization to estimate its position. Each robot senses the change in the environment with respect to a current map, initially built with a SLAM method, and constructs a temporary map which will be merged into the current map using localization information and line features of the map. This procedure enables the creation of long-term mapping robot systems for facility logistics.
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Acknowledgements
The authors were partially funded by Deutsche Forschungsgemeinschaft (DFG) within the Collaborative Research Center SFB 876, project B2 (the study was also performed in collaboration with project B4) and the European Union Horizon 2020 Programme (Horizon2020/2014–2020), under grant agreement number 688380 “VaVeL: Variety, Veracity, VaLue: Handling the Multiplicity of Urban Sensors”.
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Shaik, N., Liebig, T., Kirsch, C., Müller, H. (2017). Dynamic Map Update of Non-static Facility Logistics Environment with a Multi-robot System. In: Kern-Isberner, G., Fürnkranz, J., Thimm, M. (eds) KI 2017: Advances in Artificial Intelligence. KI 2017. Lecture Notes in Computer Science(), vol 10505. Springer, Cham. https://doi.org/10.1007/978-3-319-67190-1_19
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DOI: https://doi.org/10.1007/978-3-319-67190-1_19
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