Robotic Systems for UK Horticulture: Developing Safe, Validated Interaction Frameworks for Autonomous Crop Harvesting

This project is one of five opportunities being advertised by Harper Adams University as part of our annual competition for a funded PhD studentship. The successful candidate will receive a studentship consisting of full tuition fee coverage, a stipend and approved research costs.

UK horticulture is facing an unprecedented convergence of challenges: persistent labour shortages, rapidly rising production costs, and mounting environmental and regulatory pressures. High-value fruit crops remain especially vulnerable. Unlike arable systems, these crops rely on delicate, skilled manual handling within dense and variable canopies – tasks that current mechanised systems cannot reliably perform. As a result, the sector faces increasing risk within national food supply chains and limited capacity for sustainable growth.

At the same time, the UK has demonstrated global leadership in autonomous agriculture through initiatives such as the Hands Free Hectare and Hands Free Farm projects, which proved that fully autonomous field operations are achievable. However, translating this success into horticulture requires a new generation of robotic systems capable of interacting with crops in ways that respect biological fragility, uneven terrain, and human-centred crop architectures. A critical barrier remains: there is currently no validated scientific framework that defines safe, reliable and efficient robot-crop interaction in real horticultural environments.

This PhD project will address that fundamental gap. The researcher will develop a robust, evidence-based framework governing how robotic systems approach, assess and harvest horticultural crops. Working with advanced robotic platforms available at Harper Adams University, the project combines robotic engineering, biological crop analysis, and autonomous systems research to tackle one of the most significant technological challenges in modern agriculture.

The project has four major components:

1. Interaction Mapping
   The student will decompose the fruit-harvesting task into measurable stages – from navigating within orchard rows, to fruit detection and ripeness assessment, to stable manipulation during reaching and detachment. Biological and mechanical indicators such as fruit damage, branch disturbance and stability margins will be quantified to understand how robotic systems interact with crop environments.
2. Digital Twin Development
   A spatially accurate digital twin of orchard conditions will be created to simulate crop variability, predict interaction forces and evaluate system stability and safety under differing terrain and canopy scenarios. This will generate a replicable methodology for reducing real-world deployment risk and improving commercial and regulatory confidence in autonomous agricultural systems.
3. Field Validation
   Through controlled orchard trials, the project will quantify harvesting success rates, crop damage, operational reliability, system efficiency and safe human-robot interaction margins. Statistical evaluation will characterise performance robustness under genuine environmental variability.
4. Deployment and Impact Pathway
   Findings will be synthesised into a validated robot-crop interaction framework, including deployment guidelines for growers, technology developers and regulators. The resulting evidence base will form a crucial step toward scalable, commercially viable autonomous horticulture.

Significance

This project offers an exceptional opportunity for a researcher interested in robotics, autonomous systems or precision agriculture to contribute to the next major breakthrough in agri-technology. Its outcomes will support the ongoing impact narrative of the Hands Free Farm initiative and contribute directly to national priorities surrounding food security, labour resilience and sustainable intensification.

The successful candidate will produce high-impact scientific outputs and help shape the UK’s pathway toward fully autonomous horticultural production systems.