# Field Robot for High-throughput and High-resolution 3D Plant Phenotyping

arXiv: https://arxiv.org/abs/2310.11516 · HTML: https://mlsanity.com/paper/2310.11516/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 17 Oct 2023.

## Built on by (most cited first, 7 of 7)

- [Wheat3DGS: In-field 3D Reconstruction, Instance Segmentation and Phenotyping of Wheat Heads with Gaussian Splatting](https://mlsanity.com/paper/2504.06978/) (2025)
- [PanicleNeRF: low-cost, high-precision in-field phenotypingof rice panicles with smartphone](https://mlsanity.com/paper/2408.02053/) (2024)
- [A Survey on 3D Reconstruction Techniques in Plant Phenotyping: From Classical Methods to Neural Radiance Fields (NeRF), 3D Gaussian Splatting (3DGS), and Beyond](https://mlsanity.com/paper/2505.00737/) (2025)
- [GrowSplat: Constructing Temporal Digital Twins of Plants with Gaussian Splats](https://mlsanity.com/paper/2505.10923/) (2025)
- [Botany-Bot: Digital Twin Monitoring of Occluded and Underleaf Plant Structures with Gaussian Splats](https://mlsanity.com/paper/2510.17783/) (2025)
- [Iterative Motion Compensation for Canonical 3D Reconstruction from UAV Plant Images Captured in Windy Conditions](https://mlsanity.com/paper/2510.15491/) (2025)
- [Recent Advances in Agentic Agri-Robotic Phenotyping: A Perspective Review from Fragmented Multimodal Sensing to Unified PhenoAgent Intelligence](https://mlsanity.com/paper/2609.34567/) (2026)

## Abstract (arXiv)

With the need to feed a growing world population, the efficiency of crop production is of paramount importance. To support breeding and field management, various characteristics of the plant phenotype need to be measured -- a time-consuming process when performed manually. We present a robotic platform equipped with multiple laser and camera sensors for high-throughput, high-resolution in-field plant scanning. We create digital twins of the plants through 3D reconstruction. This allows the estimation of phenotypic traits such as leaf area, leaf angle, and plant height. We validate our system on a real field, where we reconstruct accurate point clouds and meshes of sugar beet, soybean, and maize.