Fleet Management of Autonomous Agricultural Robots with Human Awareness

Fleet Management of Autonomous Agricultural Robots is fundamental to fully autonomous farming practices as it addresses the issues of conflict resolution, resource and efficiency optimization when dealing with a fleet of homogenous or heterogenous robots. The abstract of the proposal for this PhD would be integrating human behaviour models with the navigation and task allocation system of autonomous fleets for better path planning evading possible conflicts and deadlock situations between robot-robot and human-robot(s). The study will focus on the proxemics, human behaviour modelling using decision prediction and neuroscientific methods, path planning, fleet coordination and human robot ethics. The ideas proposed in the study are planned to be first tested out using a suitable computer simulation software with the help of real world data of human navigation and behavioural patterns as needed. The simulation environment shall be an agricultural one with realistic representations of autonomous agri-robots like Thorvald (by Saga Robotics). As a part of more advanced research the successful ideas obtained through computer simulation shall be tested through implantation on similar real robots in an agricultural environment with human participation. The results obtained shall be used for evaluation, revision and improvisation of the proposed ideas.

The collection of human navigation data from the real world shall come up after a few months during the implementation phase of the project. There is a risk of its feasibility due to the ongoing COVID pandemic, as a risk mitigation strategy, if the conditions do not improve well enough to enable this data collection possible, existing scientific data of human behavioural models shall be used for the computer simulations and shall be replaced with real data when data collection becomes possible again.

The proposed CDT provides a unique vision of advanced RAS technologies embedded throughout the food supply chain, training the next generation of specialists and leaders in agri-food robotics and providing the underpinning research for the next generation of food production systems. These systems in turn will support the sustainable intensification of food production, the national agri-food industry, the environment, food quality and health.

RAS technologies are transforming global industries, creating new business opportunities and driving productivity across multiple sectors. The Agri-Food sector is the largest manufacturing sector of the UK and global economy. The UK food chain has a GVA of £108bn and employs 3.6m people. It is fundamentally challenged by global population growth, demographic changes, political pressures affecting migration and environmental impacts. In addition, agriculture has the lowest productivity of all industrial sectors (ONS, 2017). However, many RAS technologies are in their infancy - developing them within the agri-food sector will deliver impact but also provide a challenging environment that will significantly push the state of art in the underpinning RAS science. Although the opportunity for RAS is widely acknowledged, a shortage of trained engineers and specialists has limited the delivery of impact. This directly addresses this need and will produce the largest global cohort of RAS specialists in Agri-Food.

The impacts are multiple and include;

1) Impact on RAS technology. The Agri-Food sector provides an ideal test bed to develop multiple technologies that will have application in many industrial sectors and research domains. These include new approaches to autonomy and navigation in field environments; complex picking, grasping and manipulation; and novel applications of machine learning and AI in critical and essential sectors of the world economy.

2) Economic Impact. In the UK alone the Made Smarter Review (2017) estimates that automation and RAS will create £183bn of GVA over the next decade, £58bn of which from increased technology exports and reshoring of manufacturing. Expected impacts within Agri-Food are demonstrated by the £3.0M of industry support including the world largest agricultural engineering company (John Deere), the multinational Syngenta, one of the world's largest robotics manufacturers (ABB), the UK's largest farming company owned by James Dyson (one of the largest private investors in robotics), the UK's largest salads and fruit producer plus multiple SME RAS companies. These partners recognise the potential and need for RAS (see NFU and IAgrE Letters of Support).

3) Societal impact. Following the EU referendum, there is significant uncertainty that seasonal labour employed in the sector will be available going forwards, while the demographics of an aging population further limits the supply of manual labour. We see robotic automation as a means of performing onerous and difficult jobs in adverse environments, while advancing the UK skills base, enabling human jobs to move up the value chain and attracting skilled workers and graduates to Agri-Food.

4) Diversity impact. Gender under-representation is also a concern across the computer science, engineering and technology sectors, with only 15% of undergraduates being female. Through engagement with the EPSRC ASPIRE (Advanced Strategic Platform for Inclusive Research Environments) programme, AgriFoRwArdS will become an exemplar CDT with an EDI impact framework that is transferable to other CDTs.

5) Environmental Impact. The Agri-food sector uses 13% of UK carbon emissions and 70% of fresh water, while diffuse pollution from fertilisers and pesticides creates environmental damage. RAS technology, such as robotic weeders and field robots with advanced sensors, will enable a paradigm shift in precision agriculture that will sustainably intensify production while minimising environmental impacts.