Abstract
Simultaneous Localization and Mapping (SLAM) for UAV is one of the abilities for establishing autonomous UAV. Many approaches have solved SLAM problem, but the problem on data association is yet to be solved. On one hand, high data ambiguous occurs from noise measurement and unknown data collection leads to failure hypothesis. On the other hand, computational complexity still becomes challenging research in SLAM. This paper deliveres a conceptual framework to solve data association problem with low computational complexity. The framework proposes dynamic path planning using L+Dumo algorithm to solve problem in SLAM. It is expected that the develop algorithm can solve data association problem with low computational complexity.