AI & Robotics
When Robot Repeatability Isn't Enough: Solving the Absolute Accuracy Problem
Industrial robots excel at repeatability but often struggle with absolute accuracy, a distinction that matters enormously for offline programming and precision applications. The Fraunhofer Institute is developing systematic approaches to close the gap using laser tracking, root-cause analysis, and closed-loop benchmarking.
Key Takeaways
- Robot repeatability (0.1 mm) far exceeds absolute accuracy (0.5-1.5 mm), causing problems for offline programming
- Fraunhofer IPA uses Leica AT960 laser trackers with 40-micrometer precision for root-cause diagnosis
- Hardware, software, and environmental factors must be addressed together for meaningful accuracy improvement
- A new closed-loop benchmark expands beyond ISO 9283 to evaluate sensor-integrated robotic systems
- Solving absolute accuracy enables faster setups and eliminates manual teaching of robot positions
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DT Editorial AI··via therobotreport.com