Canon kabushiki kaisha (20240131699). 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 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
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 20240131699 titled 'ROBOT SYSTEM, LEARNING APPARATUS, INFORMATION PROCESSING APPARATUS, LEARNED MODEL, CONTROL METHOD, INFORMATION PROCESSING METHOD, METHOD FOR MANUFACTURING PRODUCT, AND RECORDING MEDIUM
Simplified Explanation
The patent application describes a robot system that learns force information, position information, and workpiece information from a worker to control the robot.
- The information processing portion of the robot system learns force information, position information, and workpiece information from a worker.
- The robot is controlled based on the output data of the learned model.
Potential Applications
This technology could be applied in industries such as manufacturing, healthcare, and construction where robots need to interact with human workers and workpieces.
Problems Solved
1. Improved safety in human-robot collaboration by allowing the robot to adapt to the force applied by the worker. 2. Enhanced efficiency in tasks where the robot needs to work in close proximity to human workers.
Benefits
1. Increased productivity by enabling seamless collaboration between robots and human workers. 2. Reduced risk of accidents and injuries in workplaces where robots are used alongside humans.
Potential Commercial Applications
Optimizing Human-Robot Collaboration in Manufacturing Processes
Possible Prior Art
One possible prior art could be the use of force sensors in robots to detect external forces and adjust their movements accordingly.
Unanswered Questions
How does the robot system ensure the accuracy of the learned model in different working conditions?
The patent application does not provide details on how the robot system adapts to varying working conditions to ensure the accuracy of the learned model.
What are the limitations of the robot system in terms of the types of tasks it can perform effectively?
The patent application does not discuss the potential limitations of the robot system in handling certain types of tasks or environments.
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.
