18543876. PROCESSING OF MEASUREMENT DATA AVAILABLE AS POINT CLOUDS WITH BETTER GENERALIZATION ACROSS THE TRAINING DATA simplified abstract (Robert Bosch GmbH)
PROCESSING OF MEASUREMENT DATA AVAILABLE AS POINT CLOUDS WITH BETTER GENERALIZATION ACROSS THE TRAINING DATA
Organization Name
Inventor(s)
Kilian Rambach of Stuttgart (DE)
David Stoeckel of Rutesheim (DE)
Maxim Tatarchenko of Berlin (DE)
PROCESSING OF MEASUREMENT DATA AVAILABLE AS POINT CLOUDS WITH BETTER GENERALIZATION ACROSS THE TRAINING DATA - A simplified explanation of the abstract
This abstract first appeared for US patent application 18543876 titled 'PROCESSING OF MEASUREMENT DATA AVAILABLE AS POINT CLOUDS WITH BETTER GENERALIZATION ACROSS THE TRAINING DATA
Simplified Explanation:
The patent application describes a method for processing measurement data presented as a point cloud in space, where each point is assigned values of one or more measured variables for a specific task. The method involves collecting and processing all values of the measured variable assigned to points to create an aggregated representation, which is then used as input to a task network to map to the required output for the task.
Key Features and Innovation:
- Processing measurement data in the form of a point cloud in space
- Aggregating values of measured variables assigned to points
- Using aggregated representations as inputs to a task network for mapping to required outputs
Potential Applications: The technology can be applied in various fields such as:
- Remote sensing
- Geographic information systems
- Environmental monitoring
- Robotics
Problems Solved: The method addresses the challenge of efficiently processing and analyzing large sets of measurement data represented as point clouds in space.
Benefits:
- Improved data processing efficiency
- Enhanced accuracy in mapping measured variables to required outputs
- Increased automation in data analysis tasks
Commercial Applications: Potential commercial uses include:
- Data analytics software for remote sensing applications
- Mapping and surveying tools for geographic information systems
- Monitoring systems for environmental agencies
Prior Art: Readers can explore prior art related to point cloud data processing methods, spatial data analysis techniques, and machine learning algorithms for data mapping tasks.
Frequently Updated Research: Stay updated on the latest advancements in point cloud data processing, spatial data analysis, and machine learning algorithms for data mapping tasks.
Questions about Point Cloud Data Processing: 1. How does the method in the patent application differ from traditional data processing techniques? 2. What are the key advantages of using aggregated representations in the task network mapping process?
Original Abstract Submitted
A method for processing measurement data which are present as a point cloud of points in space. The point cloud assigns values of one or more measured variables to each point, with regard to a predetermined task. In the method: for each measured variable, all values of the measured variable that are assigned to points of the point cloud are collected and processed to form an aggregated representation. The representation has the same dimensionality irrespective of how many points of the point cloud are assigned values of the relevant measured variable. One or more of these representations are fed as inputs to a task network. The one or more representations are mapped by the task network to the required output with regard to the predetermined task.
