Nec corporation (20240123614). LEARNING DEVICE, LEARNING METHOD, AND RECORDING MEDIUM simplified abstract
Contents
- 1 LEARNING DEVICE, LEARNING METHOD, AND RECORDING MEDIUM
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 LEARNING DEVICE, LEARNING METHOD, AND RECORDING MEDIUM - 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
LEARNING DEVICE, LEARNING METHOD, AND RECORDING MEDIUM
Organization Name
Inventor(s)
LEARNING DEVICE, LEARNING METHOD, AND RECORDING MEDIUM - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240123614 titled 'LEARNING DEVICE, LEARNING METHOD, AND RECORDING MEDIUM
Simplified Explanation
The patent application describes a learning device that includes an optimization problem calculation means and an executable state set learning means. The optimization problem calculation means calculates a function value to be a solution for an optimization problem based on an abstract system model and a detailed system model concerning a system in which a robot operates. The executable state set learning means learns an executable state set of an action of the robot to be executed by a controller based on a function value.
- Optimization problem calculation means: Calculates function value for optimization problem using evaluation function for evaluating reachability to a target state.
- Executable state set learning means: Learns executable state set of robot action for controller based on function value.
Potential Applications
This technology could be applied in the development of autonomous robots, automated systems, and intelligent controllers for various industries such as manufacturing, logistics, and healthcare.
Problems Solved
1. Improved efficiency in solving optimization problems in robotic systems. 2. Enhanced learning capabilities for robots to execute actions based on function values.
Benefits
1. Increased accuracy in reaching target states. 2. Enhanced performance and adaptability of robotic systems. 3. Streamlined decision-making processes for controllers.
Potential Commercial Applications
Optimization software for robotic systems Intelligent controllers for automated manufacturing processes
Possible Prior Art
Prior art may include existing optimization algorithms and learning techniques used in the field of robotics and automation.
Unanswered Questions
How does this technology compare to existing optimization algorithms in terms of efficiency and accuracy?
This article does not provide a direct comparison with existing optimization algorithms in the field of robotics.
What are the specific industries or applications where this technology is expected to have the most significant impact?
The article does not specify the industries or applications where this technology is expected to have the most significant impact.
Original Abstract Submitted
a learning device x mainly includes an optimization problem calculation means x and an executable state set learning means x. the optimization problem calculation means x calculates a function value to be a solution for an optimization problem which uses an evaluation function for evaluating reachability to a target state, based on an abstract system model and a detailed system model concerning a system in which a robot operates. the executable state set learning means x learns an executable state set of an action of the robot to be executed by a controller based on a function value.
