Visual-SLAM for the detection of hidden tomatoes in greenhouses by Hierarchical Localization and GLOMAPfor robotized harvesting

Visual-SLAM for the detection of hidden tomatoes in greenhouses by Hierarchical Localization and GLOMAPfor robotized harvesting

|Authors: Fernando Cañadas-Aránega, José C. Moreno, José L. Blanco-Claraco, Francisco Rodríguez

|Venue: arXiv preprint | Year: 2026

|arXiv: 2609.11766v1

Abstract

Advanced crop monitoring inside greenhouses is becoming one of the primary objectives of research centers. High-performance sensors, such as LiDAR or stereo cameras, have traditionally been employed for this purpose, though these often have a high cost. This work proposes a Visual-SLAM system using a monocular camera, which is significantly more cost-effective and specifically tailored for agricultural applications, such as mapping tomato crops in a greenhouse. Tests were carried out on a real tomato bunch, located in the Agroconnect experimental greenhouse. A ROS 2 Humble node was developed to run on the robot in order to capture images of these crops, which were then stored for offline processing. To generate a 3D mapped model for the crop in the greenhouse, the GLOMAP mapper, based on Structure-From-Motion, was integrated with the Hierarchical Localization toolbox. This initial mapping is a foundation for future, more advanced algorithms to analyze growth patterns, and optimize agricultural management. The system leverages a hierarchical localization paradigm based on a coarse-to-fine strategy: it first performs global retrieval to generate location hypotheses, then combines local features within the identified candidate regions. The results show a correct identification of the tomato cluster, correctly characterising the tomato that is occluded and inaccessible by classical vision technologies. The reconstructed 3D model was further validated against manual ground-truth measurements of fruit size, centroid position, and orientation, confirming the geometric accuracy of the proposed low-cost monocular pipeline.

Key Contributions

• Advanced crop monitoring inside greenhouses is becoming one of the primary objectives of research…
• High-performance sensors, such as LiDAR or stereo cameras, have traditionally been employed for t…
• This work proposes a Visual-SLAM system using a monocular camera, which is significantly more cos…
• Tests were carried out on a real tomato bunch, located in the Agroconnect experimental greenhouse
• A ROS 2 Humble node was developed to run on the robot in order to capture images of these crops, …

Topics

• vision
• planning

Code & Data

• GitHub repository: https://github.com/pablovela5620/hloc-g

BibTeX

@article{Cañadas-Aránega2026_260911766v1,
  title     = {Visual-SLAM for the detection of hidden tomatoes in greenhouses by Hierarchical Localization and GLOMAPfor robotized harvesting},
  author    = {Fernando Cañadas-Aránega and José C. Moreno and José L. Blanco-Claraco and Francisco Rodríguez},
  year      = {2026},
  eprint    = {2609.11766v1},
  archivePrefix = {arXiv},
  primaryClass  = {cs.RO},
  url       = {https://arxiv.org/abs/2609.11766v1}
}