# Agricultural Robotics: The Future of Robotic Agriculture

arXiv: https://arxiv.org/abs/1806.06762 · HTML: https://mlsanity.com/paper/1806.06762/

## Key facts

- Cited by 17 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 18 Jun 2018.

## Built on by (most cited first, 17 of 17)

- [PhenoBench -- A Large Dataset and Benchmarks for Semantic Image Interpretation in the Agricultural Domain](https://mlsanity.com/paper/2306.04557/) (2023)
- [A Survey of Computer Vision Technologies In Urban and Controlled-environment Agriculture](https://mlsanity.com/paper/2210.11318/) (2022)
- [The TerraByte Client: providing access to terabytes of plant data](https://mlsanity.com/paper/2203.13691/) (2022)
- [Presenting an extensive lab- and field-image dataset of crops and weeds for computer vision tasks in agriculture](https://mlsanity.com/paper/2108.05789/) (2021)
- [3D shape sensing and deep learning-based segmentation of strawberries](https://mlsanity.com/paper/2111.13663/) (2021)
- [A Deep Learning Driven Algorithmic Pipeline for Autonomous Navigation in Row-Based Crops](https://mlsanity.com/paper/2112.03816/) (2021)
- [Harnessing Artificial Intelligence for Sustainable Agricultural Development in Africa: Opportunities, Challenges, and Impact](https://mlsanity.com/paper/2401.06171/) (2024)
- [Self-Supervised Learning for Robotic Leaf Manipulation: A Hybrid Geometric-Neural Approach](https://mlsanity.com/paper/2505.03702/) (2025)
- [Using depth information and colour space variations for improving outdoor robustness for instance segmentation of cabbage](https://mlsanity.com/paper/2103.16923/) (2021)
- [Collection and Evaluation of a Long-Term 4D Agri-Robotic Dataset](https://mlsanity.com/paper/2211.14013/) (2022)
- [Autonomous Strawberry Picking Robotic System (Robofruit)](https://mlsanity.com/paper/2301.03947/) (2023)
- [Artificial Intelligence in Sustainable Vertical Farming](https://mlsanity.com/paper/2312.00030/) (2023)
- [A pipeline for multiple orange detection and tracking with 3-D fruit relocalization and neural-net based yield regression in commercial citrus orchards](https://mlsanity.com/paper/2312.16724/) (2023)
- [Horticultural Temporal Fruit Monitoring via 3D Instance Segmentation and Re-Identification using Colored Point Clouds](https://mlsanity.com/paper/2411.07799/) (2024)
- [ForgeVLA: Federated Vision-Language-Action Learning without Language Annotations](https://mlsanity.com/paper/2605.07474/) (2026)
- [Plant Species Recognition with Optimized 3D Polynomial Neural Networks and Variably Overlapping Time-Coherent Sliding Window](https://mlsanity.com/paper/2203.02611/) (2022)
- [Enabling 24-hour Agricultural Robotics: Unsupervised Day-to-Night Cross-Modal Image Translation for Nighttime Visual Navigation](https://mlsanity.com/paper/2607.12065/) (2026)

## Abstract (arXiv)

Agri-Food is the largest manufacturing sector in the UK. It supports a food chain that generates over pounds108bn p.a., with 3.9m employees in a truly international industry and exports pounds20bn of UK manufactured goods. However, the global food chain is under pressure from population growth, climate change, political pressures affecting migration, population drift from rural to urban regions and the demographics of an aging global population. These challenges are recognised in the UK Industrial Strategy white paper and backed by significant investment via a Wave 2 Industrial Challenge Fund Investment ("Transforming Food Production: from Farm to Fork"). Robotics and Autonomous Systems (RAS) and associated digital technologies are now seen as enablers of this critical food chain transformation. To meet these challenges, this white paper reviews the state of the art in the application of RAS in Agri-Food production and explores research and innovation needs to ensure these technologies reach their full potential and deliver the necessary impacts in the Agri-Food sector.