Robotic Self-Testing for Sensor Accuracy and Motion Verification
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Solution Overview
Problem
Robotic systems, particularly those with varying object characteristics, face challenges in comprehensive testing due to complex software and limited knowledge of system integrators, leading to performance issues and difficulty in diagnosing accuracy degradation over time.
Innovation Solution
An automated method for self-testing robotic systems, including position-determining mechanisms and distance sensors, which evaluates repeatability, accuracy, and functionality of robotic motion and computer programs without requiring dedicated reference standards, allowing for periodic verification and diagnosis of performance issues.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual testing by system integrators is used, then initial system setup can be performed, but comprehensive testing of complex software and hardware cannot be adequately performed
Solution Approach 1:
The robotic system performs self-testing through automated programs that evaluate its own hardware and software components. The system includes built-in testing capabilities that can autonomously assess sensor accuracy, robot positioning, tool placement, and program functionality without requiring external expert intervention for comprehensive verification.
Solution Approach 2:
The system incorporates feedback mechanisms where test results are automatically evaluated and compared against expected performance criteria. The automated testing program provides real-time feedback on system performance, identifying failures and generating diagnostic information about which components are not meeting performance requirements.
2Reliability
If comprehensive testing is performed to ensure proper system performance, then system reliability improves, but testing time and resources increase significantly
Solution Approach 1:
The system performs testing routines automatically during initial setup and periodically thereafter, before actual production work begins. This preliminary testing ensures the system is properly calibrated and functioning correctly before time-consuming production tasks start, preventing rework and ensuring quality from the outset.
Solution Approach 2:
The automated testing program can be executed continuously or periodically without interrupting normal production operations. The system maintains a continuous state of verification through scheduled self-tests, ensuring ongoing reliability while allowing production to proceed uninterrupted during testing windows.
3Ease of manufacture
If system integrators with partial knowledge of components perform testing, then initial installation can be completed, but accurate diagnosis of performance failures becomes difficult
Solution Approach 1:
The system includes built-in diagnostic capabilities that automatically identify which hardware or software components are failing performance requirements. The automated testing program generates specific diagnostic information about sensor calibration errors, robot positioning deviations, tool placement failures, and program logic errors, eliminating the need for integrators to manually trace complex failure causes.
4Adaptability or versatility
If robotic systems are used for tasks with varying object characteristics, then system versatility improves, but software complexity increases making testing more difficult
Solution Approach 1:
The automated testing program provides feedback that verifies the software correctly handles varying object characteristics. The system tests whether the control programs appropriately adjust robot motion and sensor calibration based on detected object properties such as size, orientation, and material characteristics, ensuring versatile performance across different workpieces.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Ensures comprehensive and autonomous testing of robotic systems, reducing human error and subjectivity, enabling timely detection of performance compromises and accurate identification of faulty components, thereby improving system reliability and maintenance efficiency.
Implementation Method 1
at least one distance sensor coupled to the robot arm for measuring a test surface distance
Implementation Method 2
The PELT tool held by each robot includes an ultrasonic transducer
Data Source
AI summary
Methods automatically and comprehensively self-test the operation, hardware, and programs of a robotic system to reveal problems in a robotic system. The system preferably evaluates repeatability of measurement by each distance sensor, an accuracy of measurement by each distance sensor, an accuracy of movement of any positioning joints used to position the robot arm, and an accuracy of at least one routine of the system control programs. The positioning joints may include one or more rotational joints or one or more translational joints. In some embodiments, the robotic system is a robotic pulse/echo layer thickness (PELT) system. When a robotic system has passed all of the tests, then the system performance has been verified. The inclusion of these self-tests allows a robotic PELT system owner to determine whether or not the robotic portion of a system is performing correctly.