RBD-YOLOv10: A Lightweight Small-Object Detector for Laser-Tracking Cooperative Targets
Laser trackers (LTs) are essential instruments for large-scale equipment assembly and in situ measurement. However, their cooperative targets, Spherically Mounted Retroreflectors (SMRs), are often small, highly reflective, and prone to interference in complex industrial environments, making accurate detection difficult. Compared with generic small-object detection, SMR detection during LT beam reacquisition is further challenged by specular highlights, halo-like blooming, and reflective background clutter, where SMRs may appear as minute bright spots with ambiguous boundaries. In this paper, we propose RBD-YOLOv10n, a lightweight detector tailored for SMRs based on the YOLOv10 framework. To improve robustness while keeping deployment efficient, we introduce three lightweight enhancements across the backbone, neck, and head, including RepNMSC, W-BiFPN, and DEHead. Validated on a custom SMR dataset, our method achieves an [email protected] of 93.24% and an [email protected]:0.95 of 78.45%. Notably, the model is extremely lightweight, with 1.98M parameters and a 4.30 MB weight file (stored in FP16). These results show that the proposed method outperforms representative baseline detectors in balancing accuracy and efficiency, supporting practical high-precision LT vision-based SMR reacquisition under industrial conditions.
Authors
- Dabao LAO
- Xin Wang (ORCID: https://orcid.org/0000-0001-8246-0606)
- Tianqi Chen (ORCID: https://orcid.org/0000-0002-0277-5163)
Institutions
- University of Science and Technology Beijing (CN)
Publication Details
- Journal
- Applied Sciences
- Published
- 2026-03-12
- DOI
- https://doi.org/10.3390/app16062734
- Primary Topic
- Robotics and Sensor-Based Localization
- Type
- article
- Field-Weighted Citation Impact
- 0.00