.png){kind=icon}
Return
Target-adaptive optical phased array lidar
.png){kind=icon}
PRE
AI
DOI：10.1364/PRJ.514468.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Lidar based on the optical phased array (OPA) and frequency -modulated continuous wave (FMCW) technology stands out in automotive applications due to its all -solid-state design, high reliability, and remarkable resistance to interference. However, while FMCW coherent detection enhances the interference resistance capabilities, it concurrently results in a significant increase in depth computation, becoming a primary constraint for improving point cloud density in such perception systems. To address this challenge, this study introduces a lidar solution leveraging the flexible scanning characteristics of OPA. The proposed system categorizes target types within the scene based on RGB images. Subsequently, it performs scans with varying angular resolutions depending on the importance of the targets. Experimental results demonstrate that, compared to traditional scanning methods, the target -adaptive method based on semantic segmentation reduces the number of points to about one -quarter while maintaining the resolution of the primary target area. Conversely, with a similar number of points, the proposed approach increases the point cloud density of the primary target area by about four times. (c) 2024 Chinese Laser Press
Keywords:
SOLID-STATE LIDAR
VISION
SENSOR
Journal
IF:
7.2
Papers:
2.4K
Citations:
1.3W
Organization
Cited Papers
Sincerest Form of Flattery? Product Innovation and Imitation in the European Automobile Industry
PREAI
ShareSaveShareSaveFundamental limits to depth imaging with single-photon detector array sensors.png)
SCIENTIFIC REPORTS
OAAI
SCIENTIFIC REPORTSIF3.9
OAAIShareSaveImportance of Mineralogical Data for Influencing Properties of Coke: a Reference on Si02 Polymorphs
PREAI
ShareSaveShareSaveShareSave
ShareSaveShareSave
View more