Robot Socket Alignment Using Contact Waveform Learning
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Solution Overview
Problem
Existing robot control systems face high costs and limited versatility due to the need for specialized equipment and sensors to correct end effector deviations relative to workpieces, particularly in varying conditions and complex workpieces, restricting their application to specific types of tasks.
Innovation Solution
A robot system and method that uses a sensor to detect changes in contact state between the end effector and workpiece, learns these changes through a feeling-around operation, and adjusts the end effector position using a control system, allowing for estimation and correction of deviations without requiring complex image recognition or force sensors, thus reducing costs and enhancing versatility.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a camera and image recognition system are used to correct end effector deviation, then measurement precision is improved, but device complexity and cost increase significantly
Solution Approach 1:
The patent replaces the optical/image recognition system with a force sensor-based mechanical sensing system. The force sensor detects contact force changes when the end effector touches the workpiece, and this force information is used to calculate deviation. This substitution eliminates cameras, illumination devices, and complex image processing systems while achieving comparable or sufficient measurement precision for industrial applications.
Solution Approach 2:
The patent employs a relatively simple and cost-effective force sensor instead of expensive camera systems, illumination devices, and specialized computers. The force sensor is a mature, inexpensive component that can be easily integrated into the end effector, significantly reducing system cost while maintaining functional requirements.
2Device complexity
If a force sensor is attached to the end effector for feedback control, then device complexity is reduced, but adaptability is limited due to restricted sensor arrangement and workpiece surface requirements
Solution Approach 1:
The patent implements feedback control by continuously monitoring the contact force between the end effector and workpiece. The force sensor provides real-time force information, which is fed back to the control system to calculate and correct deviation. This feedback mechanism enables the system to adapt to various workpiece conditions without requiring complex pre-programming or specialized sensors for each application.
Solution Approach 2:
The patent changes the approach from requiring specific workpiece surface geometries (C-plane conformity) to utilizing force parameter variations during contact. By monitoring changes in contact force magnitude and direction, the system can determine deviation regardless of workpiece surface shape, thereby significantly expanding adaptability to different workpiece types and configurations.
3Reliability
If specialized jigs or robot hands are provided for each work type to eliminate rattling, then reliability is improved, but adaptability decreases and cost increases
Solution Approach 1:
The patent enables the robot system to self-correct deviation through force-based sensing and control, eliminating the need for specialized jigs or fixtures for each work type. The force sensor detects contact state changes, and the control system automatically adjusts the end effector position to achieve proper alignment, making the system self-sufficient and highly adaptable across different applications.
Data Source
AI summary
A robot system and method for controlling a robot, wherein during learning, a detection unit detects, as waveform data for learning, the contact state when a socket is caused to contact a set position of the head of a bolt and is caused to rotate around the set position within a set movement range. A learning unit learns a plurality of detected sets of the waveform data for learning and writes the learning results to a determination unit. During practical operations, the determination unit recognizes the amount that the socket slips with respect to the bolt on the basis of actual waveform data indicating the change in the contact state when the socket is in contact with the head of the bolt and the written learning results.