18368027. ESTIMATION DEVICE, ESTIMATION METHOD, AND PROGRAM simplified abstract (Honda Motor Co., Ltd.)
Contents
- 1 ESTIMATION DEVICE, ESTIMATION METHOD, AND PROGRAM
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 ESTIMATION DEVICE, ESTIMATION METHOD, AND PROGRAM - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Unanswered Questions
- 1.11 Original Abstract Submitted
ESTIMATION DEVICE, ESTIMATION METHOD, AND PROGRAM
Organization Name
Inventor(s)
Takeru Goto of Wako-shi, Saitama (JP)
ESTIMATION DEVICE, ESTIMATION METHOD, AND PROGRAM - A simplified explanation of the abstract
This abstract first appeared for US patent application 18368027 titled 'ESTIMATION DEVICE, ESTIMATION METHOD, AND PROGRAM
Simplified Explanation
The patent application describes an estimation device that uses trained models to predict distribution information on second parameters based on input of actual parameters. The device then compares the predicted parameters with the actual parameters to estimate whether a mobile object should take a predetermined action.
- Acquires prediction parameters by inputting actual parameters into trained models
- Uses first trained model to output distribution information on second parameters
- Uses second trained model to output distribution information on second parameters
- Estimates whether the mobile object should take a predetermined action based on the comparison of prediction parameters with actual parameters
Potential Applications
This technology could be applied in various fields such as autonomous vehicles, robotics, predictive maintenance, and financial forecasting.
Problems Solved
1. Improved accuracy in predicting future outcomes based on current parameters 2. Enhanced decision-making processes for mobile objects
Benefits
1. Increased efficiency in decision-making for mobile objects 2. Enhanced safety and reliability in autonomous systems
Potential Commercial Applications
Optimizing logistics operations, enhancing predictive maintenance in industrial settings, improving financial forecasting models
Possible Prior Art
One possible prior art could be the use of machine learning models to predict future outcomes based on current parameters in various industries.
Unanswered Questions
How does the device handle uncertainty in the prediction parameters?
The abstract does not provide information on how the device deals with uncertainty in the prediction parameters. It would be interesting to know if there are any mechanisms in place to account for uncertainty in the predictions.
What is the computational complexity of the trained models used in the device?
The abstract does not mention the computational complexity of the trained models. Understanding the computational requirements of the device could provide insights into its scalability and real-time performance.
Original Abstract Submitted
Provided is an estimation device configured to: acquire prediction parameters, which are distribution information on second parameters, by inputting actual parameters, which are first parameters, into: a first trained model, which is trained to output distribution information on second parameters in response to input of first parameters by using training data and correct data; and a second trained model, which is trained to output distribution information on second parameters in response to input of first parameters by using training data and correct data; and estimate whether or not the second mobile object is to take the predetermined action by comparing the prediction parameters with the actual parameters at a subject time of the prediction parameters.
