In the field of AI autonomous driving, accurate environment perception and positioning are the keys to reliable navigation, information decision-making, and safe driving in complex dynamic environments.
The two tasks require the acquisition and processing of highly accurate and informative data in real environments. To obtain such data, unmanned vehicles or mobile measuring vehicles are often equipped with multiple sensors, such as LiDAR or cameras.
Although LiDAR adopts the optical principle, it does not depend on light. It can operate 24 hours a day, which greatly enhances the adaptability of perception. The three-dimensional detection ability of targets increases the accuracy of detection, and it can capture both static and dynamic objects.
Here we will share an obstacle detection annotation project in 3D Point Cloud.
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