18178705. SYSTEMS AND METHODS FOR DETECTING AND LABELING OBSTACLES ALONG TRAJECTORIES OF AUTONOMOUS VEHICLES simplified abstract (Kodiak Robotics, Inc.)
Contents
SYSTEMS AND METHODS FOR DETECTING AND LABELING OBSTACLES ALONG TRAJECTORIES OF AUTONOMOUS VEHICLES
Organization Name
Inventor(s)
Yinsen Jia of New York NY (US)
Abhyuday Puri of New York NY (US)
SYSTEMS AND METHODS FOR DETECTING AND LABELING OBSTACLES ALONG TRAJECTORIES OF AUTONOMOUS VEHICLES - A simplified explanation of the abstract
This abstract first appeared for US patent application 18178705 titled 'SYSTEMS AND METHODS FOR DETECTING AND LABELING OBSTACLES ALONG TRAJECTORIES OF AUTONOMOUS VEHICLES
Simplified Explanation: The patent application describes systems and methods for detecting and labeling obstacles within a vehicle environment using sensors and LiDAR technology.
- LiDAR technology used to detect obstacles within a vehicle environment
- Data points generated from sensors coupled to the vehicle
- Obstacles detected within a LiDAR point cloud
- Patches generated for each detected obstacle
- LiDAR point cloud projected into an image for analysis
- Color and shape queries performed on the image for each obstacle
- Labels assigned to obstacles based on color and shape queries
- Obstacles labeled as either vegetation or not a pedestrian
Potential Applications: 1. Autonomous vehicles for obstacle detection and avoidance 2. Enhanced safety features in vehicles to prevent collisions 3. Urban planning for mapping vegetation and pedestrian areas
Problems Solved: 1. Improved accuracy in detecting obstacles within a vehicle environment 2. Efficient labeling of obstacles based on color and shape characteristics 3. Enhanced understanding of the surroundings for autonomous vehicles
Benefits: 1. Increased safety on the roads 2. Better navigation for autonomous vehicles 3. Streamlined urban planning processes
Commercial Applications: The technology can be utilized in the automotive industry for developing advanced driver assistance systems and autonomous vehicles. It can also be applied in urban planning and smart city initiatives for efficient mapping and management of vegetation and pedestrian areas.
Prior Art: Readers interested in exploring prior art related to this technology can start by researching LiDAR-based obstacle detection systems, sensor fusion technologies in autonomous vehicles, and computer vision algorithms for object recognition.
Frequently Updated Research: Researchers are continually working on enhancing LiDAR technology for better obstacle detection and labeling in various environments. Stay updated on advancements in sensor technologies and computer vision algorithms for the latest developments in this field.
Questions about Obstacle Detection and Labeling Technology: 1. How does LiDAR technology improve obstacle detection in vehicles? 2. What are the key factors considered in labeling obstacles based on color and shape queries?
Original Abstract Submitted
Systems and methods for detecting and labeling one or more obstacles within a vehicle environment are provided. The method may comprise generating one or more data points from one or more sensors coupled to a vehicle and, using a processor, detecting one or more obstacles within a LiDAR point cloud, generating a patch for each of the one or more detected obstacles, projecting the LiDAR point cloud into an image, performing a color query on the image for each obstacle, performing a shape query on the image for each of the one or more detected obstacles, for each of the one or more detected obstacles, determining a label for the obstacle based on one or more of the color query and the shape query and labeling the obstacle with the label. The label may indicate whether each of the one or more detected obstacles is a piece of vegetation and not a pedestrian.
