18178746. SYSTEMS AND METHODS FOR DETECTING VEGETATION ALONG TRAJECTORIES OF AUTONOMOUS VEHICLES simplified abstract (Kodiak Robotics, Inc.)
Contents
SYSTEMS AND METHODS FOR DETECTING VEGETATION 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 VEGETATION ALONG TRAJECTORIES OF AUTONOMOUS VEHICLES - A simplified explanation of the abstract
This abstract first appeared for US patent application 18178746 titled 'SYSTEMS AND METHODS FOR DETECTING VEGETATION ALONG TRAJECTORIES OF AUTONOMOUS VEHICLES
The abstract describes systems and methods for detecting and identifying vegetation within a vehicle environment using LiDAR sensors and cameras.
- LiDAR point cloud and camera image data points are generated from sensors on a vehicle.
- Obstacles are detected within the LiDAR point cloud and patches are generated for each obstacle.
- The LiDAR point cloud is projected into the camera image to represent obstacles.
- Color queries are performed on the image to determine labels for the obstacles.
- The obstacles are labeled based on the color query results.
Potential Applications: - Autonomous driving systems - Agricultural machinery for crop monitoring - Environmental monitoring for vegetation analysis
Problems Solved: - Efficient detection and identification of vegetation within a vehicle environment - Improved obstacle recognition for safe navigation
Benefits: - Enhanced safety for vehicles in detecting obstacles - Increased efficiency in vegetation identification - Potential for improved agricultural practices through crop monitoring
Commercial Applications: Title: Advanced Vegetation Detection System for Autonomous Vehicles This technology can be utilized in autonomous vehicles, agricultural machinery, and environmental monitoring systems. It has the potential to revolutionize the way vehicles detect and interact with vegetation in various industries.
Prior Art: Researchers can explore existing patents related to LiDAR technology, vegetation detection, and obstacle recognition in vehicle environments to understand the background of this innovation.
Frequently Updated Research: Researchers in the field of autonomous vehicles and agricultural technology may be conducting studies on improving vegetation detection algorithms and sensor integration for enhanced performance.
Questions about Vegetation Detection Systems: 1. How does this technology improve safety in autonomous vehicles? This technology enhances obstacle detection and identification, leading to safer navigation for autonomous vehicles. 2. What are the key advantages of using LiDAR sensors for vegetation detection? LiDAR sensors provide high-resolution data points that enable accurate detection and identification of vegetation in a vehicle environment.
Original Abstract Submitted
Systems and methods for detecting and identifying vegetation 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. The one or more data points may comprise a Light Detection and Ranging (LiDAR) point cloud generated by a LiDAR sensor and an image captured by a camera. The method may further comprise, using a processor, detecting one or more obstacles within the LiDAR point cloud, generating a patch for each of the one or more obstacles, projecting the LiDAR point cloud into the image, wherein each patch represents a region of the image for each of the one or more obstacles, performing a color query on the image for each of the one or more obstacles, determining a label for the obstacle based on the color query, and labeling the obstacle with the label.
