Title
Predicting GNSS satellite visibility from densepoint clouds.
Abstract
To help future mobile agents plan their movement in harsh environments,a predictive model has been designed to determine what areas would be favorable for Global Navigation Satellite System (GNSS) positioning. The model is able to predict the number of viable satellites for a GNSS receiver, based on a 3D point cloud map and a satellite constellation. Both occlusion and absorption effects of the environment are considered. A rugged mobile platform was designed to collect data in order to generate the point cloud maps. It was deployed during the Canadian winter known for large amounts of snow and extremely low temperatures. The test environments include a highly dense boreal forest and a university campus with high buildings. The experiment results indicate that the model performs well in both structured and unstructured environments
Year
Venue
DocType
2019
arXiv: Robotics
Journal
Volume
Citations 
PageRank 
abs/1904.07837
0
0.34
References 
Authors
0
5
Name
Order
Citations
PageRank
Philippe Dandurand100.68
Philippe Babin201.35
Vladimir Kubelka3394.85
Philippe Giguère414521.51
François Pomerleau541026.35