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  4. Dynamic map update of non-static facility logistics environment with a multi-robot system
 
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2017
Conference Paper
Title

Dynamic map update of non-static facility logistics environment with a multi-robot system

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.
Author(s)
Shaik, Nayabrasul
Liebig, Thomas
Kirsch, Christopher
Fraunhofer-Institut für Materialfluss und Logistik IML  
Müller, Heinrich
Mainwork
KI 2017. Advances in artificial intelligence  
Conference
Annual German Conference on Artificial Intelligence (KI) 2017  
DOI
10.1007/978-3-319-67190-1_19
Language
English
Fraunhofer-Institut für Materialfluss und Logistik IML  
Keyword(s)
  • artificial intelligence

  • multi-robot system

  • autonomous robot

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