Cognitive Navigation for Indoor Environment Using Floorplan
Jun Li, Chee Leong Chan, Jian Le Chan, Zhengguo Li, Kong Wah Wan, Wei Yun Yau
Abstract
The recent years have seen the increasing importance of cognitive models for improved robot navigation. In this paper, a novel cognitive navigation package, which consists of topometric map representation and a three-level path planner, is proposed. The topometric maps are built from architectural floor plans with additional features within a limited number of selected regions. The inherent discrepancies between floor plans and the robot’s actual sensory readings are handled by the three-level path planner. The unique feature of this approach is that accurate localization is only required at the selected regions. At the other regions the robot will rely on the guiding directions towards the goal rather than on its accurate position on the map for navigation. Experiments show that our approach can endow a robot with capability for semantic interpretation and localization in unseen and dynamic environments.
BibTeX
@inproceedings{iros2021_cognitivenavigat,
title = {Cognitive Navigation for Indoor Environment Using Floorplan},
author = {Jun Li and Chee Leong Chan and Jian Le Chan and Zhengguo Li and Kong Wah Wan and Wei Yun Yau},
booktitle = {IROS 2021},
year = {2021}
}