📋 Case Study
3D Vision-Guided Bin-Picking for Aerospace Fastener Kits
Highly reflective titanium fasteners (M3–M8), nested geometry, dense packing, and strict traceability requirements
🏗️ Project Overview
Automated kitting cell for Boeing 787 wing assembly line
🎯 Challenge
Highly reflective titanium fasteners (M3–M8), nested geometry, dense packing, and strict traceability requirements
🔧 Design Approach
Structured light scanner with multi-angle capture; point cloud denoising using bilateral filtering + RANSAC segmentation; gripper pose optimization with grasp quality metric (Q-value) ≥ 0.82
📐 Design Diagram
AI-generated project design illustration
📐 Key Calculations
Point Cloud Density Requirement
≥ 12 pts/mm² for sub-mm grasp precision
Result: 18.7 pts/mm²
Enables accurate centroid and normal vector estimation
Grasp Success Probability
P = exp(−β × (1−Q))
Result: 98.1%
Validated against 12,000 pick attempts
📊 Results
99.2% first-attempt success rate; 100% serialization traceability via vision-verified QR code scan pre-grasp; 3.2× faster than manual kitting💡 Lessons Learned
- •Multi-angle structured light eliminated shadowing on concave fastener heads
- •Bilateral filtering preserved sharp edges while removing laser speckle noise
- •Q-value thresholding prevented low-confidence grasps that caused jamming
✅ Key Takeaways
- 1Multi-angle structured light eliminated shadowing on concave fastener heads
- 2Bilateral filtering preserved sharp edges while removing laser speckle noise
- 3Q-value thresholding prevented low-confidence grasps that caused jamming
📐 Prerequisites
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🔗 Engineering Applications
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