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Vision-Based Real-Time 3-D Position Sensor for Spherical Actuators Using ICP Pose Estimation
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- Authors
- Minoh Jeong, Junkyu Kim, Kyu-Sung Lee, Minki Kim
- Issue Date
- 2026-05
- Citation
- IEEE Sensors Journal, v.26, no.9, pp.14024-14034
- ISSN
- 1530-437X
- Publisher
- IEEE
- Language
- English
- Type
- Journal Article
- Abstract
- This article presents a vision-based real-time 3-D position sensor for spherical actuators using iterative closest point (ICP) pose estimation. Unlike conventional rotary motors with fixed axes, spherical actuators enable omnidirectional rotation, which makes traditional 1-D sensing methods, such as encoders, Hall sensors, and resolvers, unsuitable for accurate orientation measurement. To address this challenge, we propose a noncontact sensing approach that reconstructs 3-D surface point clouds from monocular camera images and estimates the full 3-D orientation of the spherical rotor. Arbitrary and nonuniform visual patterns are applied to the rotor surface, and both intentional patterns and natural surface imperfections (e.g., scratches, dust, and wear) are exploited as geometric features for pose estimation. Edge features are extracted using Canny edge detection, reconstructed into 3-D point clouds through a geometrically consistent mapping model, and aligned via ICP to estimate the spherical angles θ and φ. Experimental validation is conducted using a spherical rotor with a diameter of 15 cm. Under single-axis rotations, a minimum mean absolute error (MAE) of 0.45° in θ is achieved after pixel-per-revolution calibration. Under dynamic multiaxis rotational motions, the estimated tangential azimuth direction φ exhibits compact zero-centered error distributions within approximately 0.2°-0.9°, confirming consistent 3-D directional estimation. Longterm stability analysis further shows that cumulative angular error accumulation remains approximately 0.15° per degree under appropriate sensing conditions. A computational architecture comparison demonstrates the feasibility of real-time operation. The complete processing pipeline, including image preprocessing, 3-D reconstruction, and ICP-based pose estimation, achieves a total processing time below 32 ms per frame, satisfying real-time requirements at 30 fps. These results confirm that the proposed vision-based sensor provides a robust, noncontact, and practical solution for real-time 3-D orientation sensing in spherical actuator systems.
- Keyword
- 3-D position estimation, iterative closest point (ICP), spherical actuators, vision-based sensing
- KSP Keywords
- 3-D position estimation, 3d reconstruction, Canny Edge Detection, Computational Architecture, Consistent Mapping, Edge features, Error accumulation, Geometric features, Hall sensor, Image Preprocessing, Mapping model