Bilingual (English / 日本語) end-to-end manual for the 3D Gaussian Splatting capture-to-phenotyping pipeline: environment setup, video processing, COLMAP SfM, 3DGS training, rendering, and automated trait extraction — with parameters and troubleshooting.
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Bilingual (日本語 / English) manual and toolkit for time-series greenhouse crop data collection and annotation for 3D plant phenotyping — setup, capture geometry, ground-truth measurement, annotation, QC, and ready-to-use logging templates.
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Published in IEEE GCCE 2025, Osaka, Japan, 2025
A low-cost, self-charging autonomous ground vehicle for greenhouse monitoring, achieving 100% autonomous docking and direct-contact charging 58.4% faster than wireless.
Recommended citation: AL Zobaer, et al. (2025). "A Low-Cost Autonomous UGV with Self-Charging Capability for Efficient Greenhouse Monitoring." IEEE GCCE 2025, Osaka, Japan.
Published in ISFAR-SU 2026, 2026
A vision-navigated UGV with adjustable multi-viewpoint capture that provides the angular coverage needed for high-quality 3D reconstruction in greenhouses.
Recommended citation: AL Zobaer, et al. (2026). "Multi-Viewpoint Autonomous Capture Platform for 3D Reconstruction in Greenhouse Environments." ISFAR-SU 2026.
Published in Computers and Electronics in Agriculture (under review), 2026
A scale-invariant, render-space method that measures plant traits from 3DGS renders, achieving a 2.86× improvement in cross-session stability (CV 28.0% → 9.8%), validated over 49 days in a commercial greenhouse.
Recommended citation: AL Zobaer, et al. (2026). "Scale-Invariant Render-Space Phenotyping for Time-Series Crop Monitoring with 3D Gaussian Splatting." Computers and Electronics in Agriculture (under review).