Food chain: 5 key challenges in Robotics and Autonomous Systems in UK

Agri-Food is the UK’s largest manufacturing sector. It supports a food chain with over £ 108 billion in turnover, 3.9 million in a truly international industry, and exports £ 20 billion of manufactured goods. The global food chain is under tremendous pressure from population growth, climate change, migration policy pressures, urban, rural drift populations, and aging world demographics.

Robotics autonomous systems (RAS) and related digital technologies are enabling this critical food chain transformation. Opportunities for the RAS range include: development of field robots supporting workers by transporting payloads and operations such as crop and animal detection, weeding and boiling; integration of autonomous systems in existing farm operating equipment such as tractors; robotic systems for harvesting crops and conducting complex extrusive operations; RAS technology has the potential to be used in the field. It, however, needs to overcome the following challenges.

1. UK RAS is small and full of interest in agri-food. Defragmentation and then community expansion is urgently needed.

2. The UK RAS community has no specific training paths or doctoral training centers to provide trained agri-food human resources.

3. While substantial government investment has been made in high-tech readiness (TRL) translation activities, there is insufficient ongoing basic research in low-TRL agri-food RAS to underpin industry innovations.

4. There are concerns that RAS for AgriFood is not fully realized because the projects are too small and too small. The complex integration of different discrete technologies (e.g., navigation, security operation, grasping and manipulation, perception) often involves RAS challenges. These discreet technologies must be further developed, but large-scale industrial applications must also be provided to solve integration and interoperability problems. The UK community must undertake some well-selected large and collaborative “moon shooting” projects.

5. Successful delivery of RAS projects in Agri-Food requires close collaboration between RAS and academic and industry professionals. For example, crop breeding with new phenotypes such as fruit that robots can easily see and pick can simplify and speed RAS technologies. Therefore, it is urgent to seek new ways to develop RAS and Agri-Food domain networks that can work together to address critical challenges. This is particularly important for Agri-Food, as sector success requires very complex cross-disciplinary activities. Moreover, many of UKRI’s Research Councils and Innovate UK directly fund various aspects of Agri-Food, but no coordinated, integrated agri-food research policy has yet been established.

To overcome these challenges, research and innovation needs include developing robust, farm-friendly platforms and enhancing sensing and perception capacity, planning and coordination, manipulation and grasping, learning and adaptation, robotics interoperability, and human/robot cooperation.

Technology adoption may occur in measured steps. Most farmers and food producers will need technology that can be phased in with and within their existing production systems. Thus, people and robots often collaborate in the foreseeable future, and this collaboration must be safe. A transition period during which people and robots work together is initially simple, then more complex workpieces, driving productivity and enabling human jobs to upgrade the value chain.