What is the best grid-map for self-driving cars localization? An evaluation under diverse types of illumination, traffic, and environment
作者：
Highlights：
• Localization with occupancy or reflectivity grid maps is more accurate.
• Semantic grid maps lead to stable and reasonably accurate localization.
• Localization with colour grid maps failed due to changes in illumination.
• Entropy correlation coefficient is not a good metric for comparing colour maps.
• The two-step mapping technique was successfully employed in all experiments.
摘要
•Localization with occupancy or reflectivity grid maps is more accurate.•Semantic grid maps lead to stable and reasonably accurate localization.•Localization with colour grid maps failed due to changes in illumination.•Entropy correlation coefficient is not a good metric for comparing colour maps.•The two-step mapping technique was successfully employed in all experiments.
论文关键词：Robotics,Self-Driving Cars,Localization,Mapping,Grid Maps
论文评审过程：Received 19 September 2020, Revised 10 April 2021, Accepted 17 April 2021, Available online 22 April 2021, Version of Record 4 May 2021.
论文官网地址：https://doi.org/10.1016/j.eswa.2021.115077
