Canon kabushiki kaisha (20240227180). ROBOT SYSTEM, LEARNING APPARATUS, INFORMATION PROCESSING APPARATUS, LEARNED MODEL, CONTROL METHOD, INFORMATION PROCESSING METHOD, METHOD FOR MANUFACTURING PRODUCT, AND RECORDING MEDIUM simplified abstract
Contents
- 1 ROBOT SYSTEM, LEARNING APPARATUS, INFORMATION PROCESSING APPARATUS, LEARNED MODEL, CONTROL METHOD, INFORMATION PROCESSING METHOD, METHOD FOR MANUFACTURING PRODUCT, AND RECORDING MEDIUM
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 ROBOT SYSTEM, LEARNING APPARATUS, INFORMATION PROCESSING APPARATUS, LEARNED MODEL, CONTROL METHOD, INFORMATION PROCESSING METHOD, METHOD FOR MANUFACTURING PRODUCT, AND RECORDING MEDIUM - A simplified explanation of the abstract
- 1.4 Original Abstract Submitted
ROBOT SYSTEM, LEARNING APPARATUS, INFORMATION PROCESSING APPARATUS, LEARNED MODEL, CONTROL METHOD, INFORMATION PROCESSING METHOD, METHOD FOR MANUFACTURING PRODUCT, AND RECORDING MEDIUM
Organization Name
Inventor(s)
KAZUHIKO Shinagawa of Tokyo (JP)
YUICHIRO Kudo of Kanagawa (JP)
MOTOHIRO Horiuchi of Kanagawa (JP)
ROBOT SYSTEM, LEARNING APPARATUS, INFORMATION PROCESSING APPARATUS, LEARNED MODEL, CONTROL METHOD, INFORMATION PROCESSING METHOD, METHOD FOR MANUFACTURING PRODUCT, AND RECORDING MEDIUM - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240227180 titled 'ROBOT SYSTEM, LEARNING APPARATUS, INFORMATION PROCESSING APPARATUS, LEARNED MODEL, CONTROL METHOD, INFORMATION PROCESSING METHOD, METHOD FOR MANUFACTURING PRODUCT, AND RECORDING MEDIUM
The abstract of the patent application describes a robot system that includes a robot and an information processing portion. The information processing portion learns force information, position information, and workpiece information from a worker to control the robot based on the learned model.
- The robot system includes a robot and an information processing portion.
- The information processing portion learns force information, position information, and workpiece information from a worker.
- The learned model is used to control the robot based on the acquired data.
Potential Applications: - Manufacturing industry for automated assembly processes - Healthcare industry for robotic assistance in surgeries - Construction industry for heavy lifting tasks
Problems Solved: - Enhances efficiency in repetitive tasks - Reduces the risk of human error - Improves safety in hazardous work environments
Benefits: - Increased productivity - Precision in task execution - Cost savings in labor expenses
Commercial Applications: Title: "Robotic Automation System for Enhanced Productivity" This technology can be utilized in various industries such as manufacturing, healthcare, and construction for improved efficiency and safety. The market implications include increased demand for robotic automation solutions.
Prior Art: Researchers can explore existing patents related to robotic systems, force sensing technologies, and machine learning algorithms for further insights into this technology.
Frequently Updated Research: Stay updated on advancements in force sensing technologies, machine learning algorithms, and robotic automation systems for potential improvements in the field.
Questions about Robot System with Information Processing: 1. How does the information processing portion of the robot system learn force information? 2. What are the key benefits of using a learned model to control the robot in this system?
Original Abstract Submitted
a robot system includes a robot, and an information processing portion. the information processing portion is configured to obtain a learned model by learning first force information about a force applied by a worker to a workpiece, first position information about a position of a first portion of the worker, and first workpiece information about a state of the workpiece, and control the robot on a basis of output data of the learned model.
