Robot Fastening State Detection and Self-Correction
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Solution Overview
Problem
Existing robot systems fail to effectively handle assembly failures, particularly when fastening screws, as they do not properly detect and remove unsupplied or incorrectly fastened operation members, leading to subsequent operation failures.
Innovation Solution
A robot system equipped with imaging units and a control unit that determines the state of fastening based on captured images, allowing for the removal of operation members from the operation execution unit when fastening has failed, and automatically supplies and re-fastens new operation members without user intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the robot performs the next operation regardless of assembly failure, then the operation continues without interruption, but subsequent operations may fail due to remaining operation members
Solution Approach 1:
The patent implements a feedback mechanism where the robot captures images of the assembly position, detects whether operation members remain after assembly failure, and uses this information to determine subsequent actions. The control unit processes image data to identify the presence of remaining screws or operation members, then adjusts the operation sequence accordingly, creating a closed-loop control system that adapts to actual assembly outcomes.
Solution Approach 2:
The robot autonomously detects assembly failures through image processing and automatically removes remaining operation members without human intervention. The system performs self-diagnosis by analyzing captured images to determine if fastening succeeded or failed, and self-corrects by executing removal operations when failures are detected, enabling the system to service itself during the assembly process.
2Reliability
If the robot removes the operation member after detecting assembly failure, then subsequent operations can proceed successfully, but additional time is required for detection and removal
Solution Approach 1:
The patent captures images of the assembly position immediately after the assembly operation completes, performing detection before proceeding to the next operation. This preliminary detection allows the system to identify assembly failures early and execute removal operations promptly, preventing delays in subsequent operations and minimizing overall time loss.
Solution Approach 2:
The patent replaces manual inspection and removal operations with an automated image processing system. The control unit uses image recognition algorithms to detect the presence of remaining operation members, substituting mechanical or human detection methods with optical sensing and computational analysis, which reduces detection time and improves accuracy.
3Ease of operation
If the robot supplies a new operation member without removing the remaining one, then the supply operation can proceed, but the new operation member cannot be properly supplied due to the remaining member
Solution Approach 1:
The system uses image feedback to determine whether removal operations are necessary before re-supplying operation members. The control unit analyzes captured images to detect remaining members, and only proceeds with re-supply operations when removal is confirmed necessary, creating a conditional workflow that adapts to the actual assembly state and prevents supply failures.
Data Source
AI summary
A robot includes an operation execution unit; and a control unit which controls the operation execution unit, in which the control unit assembles an operation member at an assembly position by the operation execution unit and determines a state of fastening based on a captured image including the assembly position.