Huawei technologies co., ltd. (20240202964). METHOD AND APPARATUS FOR DETERMINING A POSE OF A VEHICLE, AND VEHICLE CONTAINING SAME simplified abstract
Contents
- 1 METHOD AND APPARATUS FOR DETERMINING A POSE OF A VEHICLE, AND VEHICLE CONTAINING SAME
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 METHOD AND APPARATUS FOR DETERMINING A POSE OF A VEHICLE, AND VEHICLE CONTAINING SAME - 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
METHOD AND APPARATUS FOR DETERMINING A POSE OF A VEHICLE, AND VEHICLE CONTAINING SAME
Organization Name
Inventor(s)
METHOD AND APPARATUS FOR DETERMINING A POSE OF A VEHICLE, AND VEHICLE CONTAINING SAME - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240202964 titled 'METHOD AND APPARATUS FOR DETERMINING A POSE OF A VEHICLE, AND VEHICLE CONTAINING SAME
Simplified Explanation
A set of unordered points associated with road markings is processed by a trained artificial neural network to determine the pose of a vehicle.
- Unordered points related to road markings are inputted into an artificial neural network.
- Non-linear regression is applied to the points to generate an output.
- The output helps determine the pose of a vehicle.
Key Features and Innovation
- Utilizes artificial neural network for processing road marking points.
- Applies non-linear regression to generate output.
- Determines vehicle pose based on the output.
Potential Applications
This technology can be used in autonomous vehicles, road maintenance, and traffic management systems.
Problems Solved
- Efficiently determines vehicle pose using road marking points.
- Enhances accuracy in vehicle positioning.
Benefits
- Improves navigation systems in vehicles.
- Enhances road safety by accurately determining vehicle pose.
Commercial Applications
- Autonomous vehicle technology
- Traffic management systems
Questions about the Technology
1. How does the artificial neural network process the unordered points?
The artificial neural network processes the unordered points by learning patterns and relationships within the data to generate an output.
2. What are the potential limitations of using non-linear regression in this context?
Non-linear regression may face challenges in handling complex data patterns and may require extensive computational resources.
Original Abstract Submitted
a set of unordered points associated with road markings is received. the unordered points are inputted to a trained artificial neural network. using the artificial neural network, an output is generated by applying non-linear regression to the unordered points. based on the output, a pose of a vehicle is determined.
