Human-Inspired Long-Term Indoor Localization in Human-Oriented Environment

Inspired by how humans navigate, required. In fact, there is a trade-off between accuracy we can exploit insights from human navigation to improve and robustness, and each task requires a different blend of long-term localization, which enables robots to navigate the two. For example, for planning and navigating along the in the same environment over extended periods, spanning path of hundreds of meters, robustness (i.e., avoiding jumps several months or even years. In this work, we summarize in the trajectory) is more important, while high accuracy our past contributions to robust long-term localization and is only required in specific end-points (i.e.