Incorporating Hierarchical Information for UAV based Semantic Mapping

Power, size and weight are major constraining factors for UAVs, which have caused researchers to investigate alternative information representations, such as semantics, to reduce the computational load onboard UAVs. However, the connection between spatial and semantic information has not been fully explored and the literature on including semantic information for UAV navigation is limited. This paper provides a new taxonomy on spatial and semantic relations through consideration of a selected subset of the literature. Concepts of semantic information are related with spatial maps and two hypotheses for improving algorithms based on the literature are generated. The algorithms are tested in numerical simulations on the task of semantic mapping and the effects of influential parameters are examined. Results indicate that a defined hierarchical structure of semantic information enables improved map reproduction. The proposed algorithm exhibits the potential to improve the use of semantic information in UAV deployment scenarios, such as agriculture, search and rescue and industrial inspections.