Finding the best hardware configuration for 2D SLAM in indoor environments via simulation based on Google Cartographer.

ABSTRACT: One of the most challenging topics in robotics is simultaneous localization and mapping (SLAM) in the indoor environments. Due to the fact that Global Navigation Satellite Systems cannot be successfully used in such environments, different data sources are used for this purpose, among others light detection and ranging (LiDARs ), which have advanced from numerous other technologies. Other embedded sensors can be used along with LiDARs to improve SLAM accuracy, e.g. the ones available in the Inertial Measurement Units and wheel odometry sensors. Evaluation of different SLAM algorithms and possible hardware configurations in real environments is time consuming and expensive. In our study, we evaluate the accuracy of mapping and localization (based on Absolute Trajectory Error and Relative Po

SUBMITTER: Sobczak L 

PROVIDER: S-EPMC9637188 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature