17101313. SYSTEMS AND METHODS FOR OBJECT DETECTION WITH LIDAR DECORRELATION simplified abstract (Ford Global Technologies, LLC)
Contents
- 1 SYSTEMS AND METHODS FOR OBJECT DETECTION WITH LIDAR DECORRELATION
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 SYSTEMS AND METHODS FOR OBJECT DETECTION WITH LIDAR DECORRELATION - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Commercial Applications
- 1.9 Prior Art
- 1.10 Frequently Updated Research
- 1.11 Questions about Autonomous Vehicle Object Detection
- 1.12 Original Abstract Submitted
SYSTEMS AND METHODS FOR OBJECT DETECTION WITH LIDAR DECORRELATION
Organization Name
Inventor(s)
Kevin Lee Wyffels of Livonia MI (US)
SYSTEMS AND METHODS FOR OBJECT DETECTION WITH LIDAR DECORRELATION - A simplified explanation of the abstract
This abstract first appeared for US patent application 17101313 titled 'SYSTEMS AND METHODS FOR OBJECT DETECTION WITH LIDAR DECORRELATION
Simplified Explanation
The patent application describes systems and methods for operating an autonomous vehicle using LiDAR data and image data to detect objects. It involves using two different object detection algorithms and modifying the detection information to improve autonomous driving operations.
- Obtaining LiDAR data and image data from the autonomous vehicle
- Using two object detection algorithms to generate detection information
- Processing the information to determine if an object was detected by both algorithms
- Modifying the first detection information based on the second detection information
- Using the modified information to enhance autonomous driving operations
Potential Applications
The technology can be applied in autonomous vehicles, robotics, surveillance systems, and other industries requiring object detection and autonomous operation capabilities.
Problems Solved
This technology addresses the challenges of accurate object detection in autonomous vehicles, improving safety and efficiency in navigation and decision-making processes.
Benefits
The benefits of this technology include enhanced object detection accuracy, improved autonomous driving performance, increased safety on the roads, and better decision-making capabilities for autonomous systems.
Commercial Applications
Title: Advanced Object Detection System for Autonomous Vehicles This technology can be utilized by autonomous vehicle manufacturers, transportation companies, security firms, and industries requiring autonomous operation capabilities to enhance their products and services.
Prior Art
There is prior art related to object detection systems in autonomous vehicles, but this patent application introduces a novel approach by combining LiDAR and image data with multiple detection algorithms to improve accuracy and performance.
Frequently Updated Research
There may be ongoing research in the field of autonomous vehicle technology, particularly in the development of advanced object detection systems and algorithms for improved autonomous driving capabilities.
Questions about Autonomous Vehicle Object Detection
How does this technology improve object detection in autonomous vehicles?
This technology improves object detection by combining LiDAR and image data with multiple detection algorithms, enhancing accuracy and performance.
What are the potential applications of this advanced object detection system?
The potential applications include autonomous vehicles, robotics, surveillance systems, and industries requiring autonomous operation capabilities.
Original Abstract Submitted
Systems/methods for operating an autonomous vehicle. The methods comprise: obtaining LiDAR data generated by a LiDAR system of the autonomous vehicle and image data generated by a camera of the autonomous vehicle; performing a first object detection algorithm to generate first object detection information using the LiDAR data, and a second object detection algorithm to generate second object detection information using both the LiDAR data and the image data; and processing the first and second object detection information to determine whether a given object was detected by both the first and second object detection algorithms. When a determination is made that the given object was detected by both the first and second object detection algorithms, the first object detection information is selectively modified based on contents of the second object detection information. The modified first object detection information is used to facilitate at least one autonomous driving operation.
