The US Patent and Trademark Office officially published a series of Project Titan patents or Apple Inc. Two of the key patents cover LiDAR systems. The first patent covers predicting LiDAR data using machine learning which is currently being used in Apple’s autonomous training vehicles. The second patent covers enabling LiDAR detection on autonomous vehicles. The third patent covers a multi-stage active suspension actuator.
According to Apple, vehicles use light detection and ranging (LiDAR) sensors to detect the nearby environment. An autonomous vehicle may use LiDAR sensors to determine objects or other vehicles on the road to determine appropriate driving actions to perform. The autonomous vehicle may also include additional sensors, such as an optical sensor (e.g., a camera) or a radar sensor, to determine additional information of the nearby environment. Although LiDAR sensors are capable of sensing environmental information in a form that is interpretable by machine learning algorithms or decision-making systems, LiDAR sensors are currently slower than existing cameras or radar sensors.
Cameras or radar sensors may be able to capture image frames or radar data frames, respectively, at a rate that is faster than a capture rate of LiDAR sensors. Thus, the autonomous vehicle may utilize image data or radar data from the cameras or radar sensors to supplement LiDAR data from LiDAR sensors. LiDAR data is in fact more robust than image data or radar data for machine learning and interpretation such that additional LiDAR data must be accessible at a rate faster than the capture rate of the LiDAR sensor.
Apple’s granted patent covers systems and methods for predicting LiDAR data at a vehicle using machine learning. In some embodiments, a vehicle may include one or more sensors, a light detection and ranging (LiDAR) sensor and a LiDAR prediction system.
