A Platform for Perception Innovation
- Detection: Identification of objects (e.g., cars, pedestrians, etc.) in the 3D point cloud and camera. The system accurately estimates their centroids, width, height and depth to generate 3D bounding boxes for the objects.
- Classification: Classifying the type of detected objects. This helps in further understanding the motion characteristics of those objects.
- Instance Segmentation: Further classifying each point in the scene to identify specific objects those points belong to. This is especially important to accurately identify finer details, such as lane divider markings on the road.
- Tracking: Tracking objects through space and time. This helps keep track of objects that could intersect the vehicle’s path.
- Range/Orientation: Identifying where the object is relative to the vehicle, and how it’s oriented relative to the vehicle. This helps the vehicle contextualize the scene around it.
- Instant True Velocity: Leveraging the benefits of agile LiDAR to capture the speed and direction of the object’s motion relative to the vehicle. This provides the foundation for motion forecasting.
- Lane Marking Detection: Detection and classification of every type of lane marking, ensuring safe vehicle navigation.
- Drivable Area: Detection of empty space in front of the vehicle until the next road obstacle (e.g., another vehicle, pedestrians etc.), as well as detection of the lane markings on either side of the vehicle or in the lane to its left or right.
- Motion Forecasting: Forecasting where the object will be at different times in the future. This helps the vehicle to assess the risk of collision and charter a safe course.