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Simultaneous localization and mapping (SLAM) technology enables autonomous vehicles to estimate their own poses and establish the map of an unknown environment according to the data collected by onboard sensors. SLAM can provide localization information to the decisionmaking module for vehicle planning, and has become one of the research hotspots of autonomous driving technology in recent years. Based on the point cloud data collected by LiDAR, this paper focuses on the SLAM technology applied in autonomous driving. The related research at home and abroad has been reviewed including the frontend odometry, the backend optimization and loop closure detection. Due to the limitations of a single sensor, the opportunities and challenges of multisensor fusion SLAM technology for autonomous driving are discussed based on the research hotspots and difficulties in the field of multisensor fusion.
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| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
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