The University of Lincoln has been awarded the Queen’s Anniversary Prize, the highest national Honour awarded to UK colleges and universities, for its work supporting the success and sustainability of the UK’s food and farming industries through innovations in research, education, and technology.

LIAT has been an exemplar for the E3 funding programme and has demonstrated best practice in rapidly scaling-up a small research group while maintaining research excellence, generating local, national, and international impact, and establishing a sustainable institute.

– Professor Dame Jessica Corner FMedSci, MAE, RN, Executive Chair of Research England

The Queen’s Anniversary Prize for Further and Higher Education is the highest National Honour for UK universities and colleges. The award represents a major accomplishment for the University and, as Vice Chancellor, I would like to express my gratitude to everyone who has supported the development of our exceptional provision in these disciplines, notably through the Lincoln Institute for Agri-food Technology. Our award is all the more remarkable given LIAT was founded less than a decade ago. It is now widely recognised as one of the leading centres for agri-robotics and related research in the world.

– Professor Neal Juster, Vice Chancellor, University of Lincoln

The E3 award enabled Lincoln Agri-Robotics to shape the future talents of five PhD students with a clear focus on designing and building intelligent agricultural robots.

Yoon Ju Cho

My PhD research focused on field-based plant phenotyping assisted by a mobile robotic phenotyping platform to evaluate radiation use efficiency in wheat, utilising3D and spectral imaging techniques. Although my primary background was in crop science, this multidisciplinary project has facilitated my acquisition and application of machine learning techniques to develop sophisticated crop modelling. I also had the opportunity to enhance my professional network and gain a broader perspective by participating in international and national conferences.

Laurence Roberts-Elliott

My PhD, funded by a LAR studentship, has focused on developing a multi-robot system for mapping soil properties in arable fields. This work aims to enable precision land management, to reduce inputs and negative environmental impacts of agriculture. I have investigated the effectiveness of combining existing and bespoke methods of informative path-planning and multi-robot coordination to autonomously decide where soil measurements should take place, and which robots to allocate to these measurement tasks.

Vishnu Rajendran Sugathakumary

In November 2020, I enrolled as a PhD candidate at LAR, embarking on a research endeavour dedicated to the development of a soft, customizable tactile sensing skin. The primary aim of this investigation was to develop such a technology and augment haptic sensations for strawberry-picking robotic end effectors. Within the esteemed research environment at LAR, I had the privilege of accessing world-class facilities which enabled the comprehensive in-house development of the sensing technology from inception to completion.

Rajitha De Silva

My PhD project focused on vision-based navigation for agricultural robots in arable fields. I have developed an AI system that can detect crop rows in any crop field and autonomously drive a robot along those rows for precision agricultural tasks. This system underwent extensive development and testing, involving over 100 hours in fields around Lincoln. The facilities at the Riseholme campus proved invaluable in supporting my research. As a PhD student at LAR, I had the opportunity to attend multiple international conferences, delivered several presentations, showcasing my research and its contributions to the field of precision agriculture.

Srikishan Vayakkattil

As a dedicated PhD student, I specialise in soft robotics with a focus on developing a revolutionary soft haptic probe. My research involves creating a system that harnesses the power of touch to comprehend and adapt to its environment. In contrast to conventional soft sensors, my approach integrates predictive models to determine optimal geometrical and mechanical parameters, significantly enhancing the efficiency of the probe. Additionally, my work extends to computer vision, where I strive to identify mechanical parameters from visual data such as videos and photos of objects, contributing to the advancement of tactile perception in robotics.

LIAT worked with specialist agricultural marketing agency Hillsgreen as part of our engagement activities. Following the success of an initial campaign, Hillsgreen was tasked with coordinating and delivering another – this campaign aimed at raising awareness about LIAT’s programs, facilities, and research excellence.