18547208. Method for Determining at Least One System State by Means of a Kalman Filter simplified abstract (Robert Bosch GmbH)

Method for Determining at Least One System State by Means of a Kalman Filter

Organization Name

Robert Bosch GmbH

Inventor(s)

Holger Digel of Kusterdingen (DE)

Simon Weissenmayer of Flein (DE)

Method for Determining at Least One System State by Means of a Kalman Filter - A simplified explanation of the abstract

This abstract first appeared for US patent application 18547208 titled 'Method for Determining at Least One System State by Means of a Kalman Filter

Simplified Explanation

The abstract describes a method for determining system states using a Kalman filter assembly, where measured values from sensors are processed through two different Kalman filters with varying settings before being fused to produce an overall estimation result.

• The method involves using a first Kalman filter to estimate the system state and outputting the estimation result along with information about its reliability.
• A second Kalman filter with different setting parameters is then used to perform a second estimation of the system state, also outputting the estimation result and information about its reliability.
• The results from the two filters are then combined to produce an overall estimation result for the system state, along with a fused reliability assessment.

Potential Applications

This technology can be applied in various fields such as:

• Robotics
• Autonomous vehicles
• Aerospace industry
• Industrial automation

Problems Solved

This method helps in:

• Improving accuracy of system state estimation
• Enhancing reliability of estimation results
• Reducing uncertainty in sensor measurements

Benefits

The benefits of this technology include:

• Enhanced system performance
• Increased efficiency in decision-making processes
• Improved overall system reliability

Potential Commercial Applications

This technology can be commercially applied in:

• Sensor technology companies
• Control systems manufacturers
• Robotics and automation industries
• Aerospace and defense sector

Possible Prior Art

One possible prior art for this technology could be the use of multiple filters with different settings to improve estimation accuracy in various systems.

How does this method compare to traditional single-filter estimation techniques?

This article does not provide a direct comparison between the proposed method and traditional single-filter estimation techniques.

What are the specific setting parameters that differentiate the first and second Kalman filters?

The abstract does not specify the exact setting parameters that are varied between the first and second Kalman filters.

Original Abstract Submitted

A method for determining at least one system state by way of a Kalman filter assembly, wherein at least one measured value measured by at least one sensor of the system is supplied to the Kalman filter assembly is disclosed. The method includes (a) performing a first estimation of the system state by way of a first Kalman filter of the Kalman filter assembly, a first estimation result and at least one associated first item of information about the reliability of the first estimation result being output, (b) performing a second estimation of the system state by way of a second Kalman filter of the Kalman filter assembly, a second estimation result and at least one associated second item of information about the reliability of the second estimation result being output, the second Kalman filter differing from the first Kalman filter in at least one setting parameter, and (c) fusing the first estimation result and the second estimation result to produce an overall estimation result for the system state, and fusing the first item of information about the reliability of the first estimation result and the second item of information about the reliability of the second estimation result to produce an overall item of information about the reliability of the overall estimation result.