Growers may have to swap straight crop rows for spirals in future, as scientists say curved layouts could make autonomous robots faster, more efficient and less damaging to soil than tractors.
Researchers from Sri Lanka’s University of Colombo and the University of Lincoln in the UK tested a “square-spiral” field design in simulations and found that it cut robot travel distances by 28% and task times by a quarter when compared with conventional row-based designs.
When several robots worked together, the new geometry improved coordination efficiency by up to 37%, suggesting significant energy and time savings in future automated farms.
Publishing their findings on the preprint platform arXiv, the researchers said field design must evolve alongside automation. “Rethinking field layout for crops to accommodate multi-robot systems is essential for sustainable and efficient robotic agriculture,” they wrote.
Fields built for tractors, not robots
Modern crop rows and headlands were designed for the turning radius and width of heavy tractors, a system that has shaped the structure of global agriculture for more than a century. But these straight, uniform rows create challenges for smaller autonomous machines, which lose time making tight turns and can struggle with repetitive visual patterns that confuse onboard cameras.
“With the growing global trend towards agricultural robotics, there is an opportunity to reduce dependence on heavy machinery by deploying lightweight autonomous robots,” the researchers said. “To achieve this, traditional crop layouts must be redesigned.”
Their proposed square-spiral pattern begins at one corner of a field and coils inward towards a central tramline, removing headlands entirely. This configuration increases the cropped area, reduces turning, and allows robots to reach any point quickly via the central access line.
Further reading
Using a vision-based navigation system and a predictive control algorithm, the researchers tested robots in both linear and spiral layouts under identical conditions. The spiral layout achieved shorter routes and faster travel times while maintaining a mean positional error of just 0.38 metres — about half that of a standard linear field.
Because the spiral can be represented as a single continuous path, the authors say it simplifies navigation by reducing a two-dimensional problem to a one-dimensional one, adding enough geometric variation for the robot to know where it is.
Multi-robot collaboration
The team also compared two coordination methods for fleets of autonomous robots working in spiral fields: a centralised “Hungarian” allocation, a mathematical model that assigns tasks in the most efficient order, and a decentralised “greedy” system, where each robot simply takes the nearest available task. The latter proved faster and more practical in the field context, cutting completion times by 33–37% while maintaining fair workload distribution across the fleet.
The researchers said the next step will be to test spiral layouts under real field conditions, combining robotics data with agronomic performance. If the design performs as simulated, it could allow autonomous robots to work faster and more efficiently while reducing soil compaction — paving the way for a new generation of field systems designed around machines that drive themselves.
Key takeaways
- Researchers tested a “square-spiral” field layout designed for autonomous robots.
- The spiral shape cut robot travel distances by 28% and task times by 25%.
- Multi-robot coordination improved by up to 37%.
- Removing tractor-style headlands reduces soil compaction and energy use.
- Developed by the University of Colombo and the University of Lincoln.
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