# Single-Shot 6DoF Pose and 3D Size Estimation for Robotic Strawberry Harvesting

arXiv: https://arxiv.org/abs/2410.03031 · HTML: https://mlsanity.com/paper/2410.03031/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 3 Oct 2024.

## Built on by (most cited first, 4 of 4)

- [6D Strawberry Pose Estimation: Real-time and Edge AI Solutions Using Purely Synthetic Training Data](https://mlsanity.com/paper/2511.11307/) (2025)
- [Category-Level 6D Object Pose Estimation in Agricultural Settings Using a Lattice-Deformation Framework and Diffusion-Augmented Synthetic Data](https://mlsanity.com/paper/2505.24636/) (2025)
- [Mind the Shape Gap: A Benchmark and Baseline for Deformation-Aware 6D Pose Estimation of Agricultural Produce](https://mlsanity.com/paper/2603.27429/) (2026)
- [From Simulation to the Real-World: An In-Field 6D Pose Dataset and Baseline for Robotic Strawberry Harvesting](https://mlsanity.com/paper/2606.11381/) (2026)

## Abstract (arXiv)

In this study, we introduce a deep-learning approach for determining both the 6DoF pose and 3D size of strawberries, aiming to significantly augment robotic harvesting efficiency. Our model was trained on a synthetic strawberry dataset, which is automatically generated within the Ignition Gazebo simulator, with a specific focus on the inherent symmetry exhibited by strawberries. By leveraging domain randomization techniques, the model demonstrated exceptional performance, achieving an 84.77% average precision (AP) of 3D Intersection over Union (IoU) scores on the simulated dataset. Empirical evaluations, conducted by testing our model on real-world datasets, underscored the model's viability for real-world strawberry harvesting scenarios, even though its training was based on synthetic data. The model also exhibited robust occlusion handling abilities, maintaining accurate detection capabilities even when strawberries were obscured by other strawberries or foliage. Additionally, the model showcased remarkably swift inference speeds, reaching up to 60 frames per second (FPS).