Robot Arm Pose Error Detection Using Multiple Pose Markers
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Solution Overview
Problem
Robot systems face challenges in accurately detecting pose errors during remote operations, which can lead to reduced operation accuracy and increased operational risks due to the inability to ensure the operating arm correctly moves to the intended position and orientation as expected by the operator.
Innovation Solution
An error detection method that involves obtaining a target pose of the operating arm, acquiring a positioning image, recognizing pose identifications on the arm, determining the actual pose, and generating a control signal when an error is detected, utilizing a computer device with a processor and image acquisition device to perform these tasks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a robot system performs remote operations with high precision requirements, then operation accuracy must be maintained, but pose detection errors can lead to deviations from intended positions and orientations
Solution Approach 1:
The patent implements a feedback mechanism by continuously detecting the operating arm's pose through multiple identification patterns, comparing actual pose with target pose, and generating control signals when deviations exceed thresholds. This closed-loop feedback ensures operation reliability by correcting pose errors in real-time during remote operations.
Solution Approach 2:
The patent changes the parameter of pose detection by using multiple identification patterns (at least three different patterns) instead of a single pattern. This multi-parameter approach improves measurement precision by providing redundant detection data and enabling more accurate determination of the operating arm's position and orientation.
2Manufacturing precision
If the operating arm moves to the intended position and orientation as expected, then operation accuracy is improved, but detection errors can cause deviations
Solution Approach 1:
The patent segments the pose identification task by using multiple separate identification patterns distributed on the operating arm instead of a single identification element. Each pattern can be independently detected and processed, improving positioning accuracy by providing multiple measurement points for calculating the operating arm's pose.
Solution Approach 2:
The patent uses multiple copies of identification patterns on the operating arm to create redundant measurement sources. These pattern copies enable cross-validation and more accurate pose calculation through multiple detection points, improving measurement accuracy for position and orientation determination.
3Reliability
If real-time pose detection is implemented, then operation safety is improved, but detection errors can lead to incorrect fault identification
Solution Approach 1:
The patent implements real-time feedback detection by continuously monitoring the operating arm's pose through multiple identification patterns and comparing actual pose with target pose. When pose errors exceed preset thresholds, control signals are generated to correct deviations, improving operation safety through continuous real-time monitoring and correction.
Solution Approach 2:
The patent improves pose detection accuracy by using multiple identification patterns as additional detection parameters. This multi-pattern approach provides redundant measurement data and enables more robust pose calculation, reducing detection errors while maintaining real-time monitoring capability for operation safety.
Data Source
AI summary
The present application relates to the field of error detection technology. An error detection method is provided. The error detection method includes: obtaining a target pose of an end of an operating arm; acquiring a positioning image; recognizing, in the positioning image, a plurality of pose identifications located on the end of the operating arm, the plurality of pose identifications including different pose identification patterns; determining an actual pose of the end of the operating arm based on the plurality of pose identifications; and generating a control signal related to a fault in response to the target pose and the actual pose meeting an error detection condition.