Semantic mapping for mobile outdoor robots
2015 14th IAPR International Conference on Machine Vision Applications (MVA)(2015)
摘要
In this paper we present the concept and realization of a semantic mapping system for a mobile outdoor robot. Semantic maps aim to give robots the ability to gather semantic information about their environment, to store it, represent it for the user, and to perform high-level tasks based on the semantic information. The map is build by a system integrating the combination of object classification and common-sense knowledge. We validate the proposed semantic map representation on a real-world 3D point cloud dataset. The presented classification approach achieves an overall precision about 96 %. The semantic maps result into a data structure which offers the opportunity to solve complex task settings and can be integrated onto real robotic systems.
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关键词
mobile outdoor robots,semantic mapping system,semantic information,high-level tasks,object classification,common-sense knowledge,semantic map representation,real-world 3D point cloud dataset,classification approach,data structure,complex task settings,robotic systems
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