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Efficient Semantic Mapping in Dynamic Environments

Unmanned Aerial Vehicles (UAVs) are required to fulfill more and more complex tasks in indoor environments like inspection, stock-taking or transportation of goods. For these tasks, they need to percept objects and obstacles in the environment, navigate safely in it and sometimes even interact with it. A step towards generating a comprehensive environmental overview for robots are semantic maps. Nevertheless, UAVs have several constraints concerning size, weight and power consumption and thus computational resources. In this paper an efficient object-oriented semantic mapping approach suitable for UAVs and similar constrained robots in dynamic environments is proposed. The approach can be completely executed on a computer suited as onboard computer of an UAV. A map comprising semantic information and dynamic objects is generated and updated with update rate of more than 10 Hz.