Nvidia corporation (20240353234). GENERATING MAPS REPRESENTING DYNAMIC OBJECTS FOR AUTONOMOUS SYSTEMS AND APPLICATIONS simplified abstract
Contents
- 1 GENERATING MAPS REPRESENTING DYNAMIC OBJECTS FOR AUTONOMOUS SYSTEMS AND APPLICATIONS
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 GENERATING MAPS REPRESENTING DYNAMIC OBJECTS FOR AUTONOMOUS SYSTEMS AND APPLICATIONS - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Key Features and Innovation
- 1.6 Potential Applications
- 1.7 Problems Solved
- 1.8 Benefits
- 1.9 Commercial Applications
- 1.10 Questions about the Technology
- 1.11 Original Abstract Submitted
GENERATING MAPS REPRESENTING DYNAMIC OBJECTS FOR AUTONOMOUS SYSTEMS AND APPLICATIONS
Organization Name
Inventor(s)
Anton Mitrokhin of Santa Clara CA (US)
Alexey Solovey of Campbell CA (US)
Tilman Wekel of San Jose CA (US)
GENERATING MAPS REPRESENTING DYNAMIC OBJECTS FOR AUTONOMOUS SYSTEMS AND APPLICATIONS - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240353234 titled 'GENERATING MAPS REPRESENTING DYNAMIC OBJECTS FOR AUTONOMOUS SYSTEMS AND APPLICATIONS
Simplified Explanation
This patent application describes a method for generating maps using sensor data and then annotating other sensor data using these maps for autonomous systems and applications.
- Automatically propagate annotations from one type of sensor data to another type of sensor data.
- Use the first sensor data to create a map of static and dynamic objects.
- Annotate the second sensor data using the map and annotations from the first sensor data.
Key Features and Innovation
- Automatic propagation of annotations between different types of sensor data.
- Creation of maps to represent static and dynamic objects.
- Annotating sensor data based on the maps and annotations from the first sensor data.
Potential Applications
This technology can be used in autonomous vehicles, surveillance systems, and robotics for accurate object detection and tracking.
Problems Solved
This technology addresses the challenge of annotating sensor data accurately and efficiently, especially in dynamic environments.
Benefits
- Improved accuracy in object detection and tracking.
- Enhanced efficiency in annotating sensor data.
- Increased reliability of autonomous systems.
Commercial Applications
- Autonomous vehicles for improved navigation and object detection.
- Surveillance systems for enhanced security and monitoring capabilities.
- Robotics for precise object manipulation and navigation.
Questions about the Technology
How does this technology improve the efficiency of autonomous systems?
This technology improves efficiency by automating the annotation process and ensuring accurate object detection.
What are the potential challenges in implementing this technology in real-world applications?
Potential challenges may include integrating different types of sensor data seamlessly and ensuring the accuracy of annotations in dynamic environments.
Original Abstract Submitted
in various examples, generating maps using first sensor data and then annotating second sensor data using the maps for autonomous systems and applications is described herein. systems and methods are disclosed that automatically propagate annotations associated with the first sensor data generated using a first type of sensor, such as a lidar sensor, to the second sensor data generated using a second type of sensor, such as an image sensor(s). to propagate the annotations, the first type of sensor data may be used to generate a map, where the map represents the locations of static objects as well as the locations of dynamic objects at various instances in time. the map and annotations associated with the first sensor data may then be used to annotate the second sensor data and/or determine additional information associated with the objects represented by the second sensors data.
