From swept contact to pose: Probe-aware registration via complementary-shape docking

2026-05-20

AI Summary

This work addresses the challenge of model-to-scene registration in high-precision robotic manipulation, where optical methods suffer from long calibration chains, line-of-sight occlusions, and manufacturing inaccuracies. To overcome these limitations, the authors propose a complementary shape docking approach that fuses contact and non-contact sensing. By explicitly modeling probe geometry and reformulating registration as a shape-matching problem between the object and the probe’s swept volume, the method avoids the fragility of traditional point correspondence and eliminates reliance on external sensors. A global search based on low-discrepancy SO(3) sampling and 3D FFT is combined with SE(3) Lie algebra optimization and analytical contact sensitivity for pose refinement. The approach achieves sub-0.04 mm/0.4° accuracy in freeform surface simulations and 0.42 mm/3.75° in dental preparation robot experiments, outperforming existing optical tracking solutions.

Abstract

Accurate registration between a prior model and the real scene is essential for high-precision robotic manipulation, yet optical methods suffer from long calibration chains, line-of-sight constraints, and fabrication errors. We propose a calibration-free alternative that reformulates contact registration as complementary-shape docking between the object and the probe's swept volume, explicitly accounting for probe geometry and leveraging both contact and non-contact evidence. Our solver integrates a global-to-local search via 3D FFT correlation over low-discrepancy SO(3) samples, then followed by continuous SE(3) refinement using Lie-algebra updates and analytic contact sensitivities. This pipeline yields efficient exploration and metric-grade convergence without fragile point correspondences. Simulation across free-form meshes achieved sub-0.04 mm and sub-0.4° accuracy and robustness to pose noise and contact loss. On a tooth-preparation robot, our method attained 0.42 mm and 3.75°, outperforming an optical tracker registration while requiring no external sensors. These results demonstrate a practical and precise registration strategy for surgical and industrial robots.

Problem

• registration
• robotic manipulation
• contact sensing
• probe-aware
• complementary-shape docking

Innovation

• complementary-shape docking
• probe-aware registration
• contact-based pose estimation
• 3D FFT correlation
• Lie-algebra refinement